mental health research students

• Open access
• Published: 20 September 2022

Factors that influence mental health of university and college students in the UK: a systematic review

• Fiona Campbell 1 ,
• Lindsay Blank 1 ,
• Anna Cantrell 1 ,
• Susan Baxter 1 ,
• Christopher Blackmore 1 ,
• Jan Dixon 1 &
• Elizabeth Goyder 1  

BMC Public Health volume  22 , Article number:  1778 ( 2022 ) Cite this article

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Worsening mental health of students in higher education is a public policy concern and the impact of measures to reduce transmission of COVID-19 has heightened awareness of this issue. Preventing poor mental health and supporting positive mental wellbeing needs to be based on an evidence informed understanding what factors influence the mental health of students.

To identify factors associated with mental health of students in higher education.

We undertook a systematic review of observational studies that measured factors associated with student mental wellbeing and poor mental health. Extensive searches were undertaken across five databases. We included studies undertaken in the UK and published within the last decade (2010–2020). Due to heterogeneity of factors, and diversity of outcomes used to measure wellbeing and poor mental health the findings were analysed and described narratively.

We included 31 studies, most of which were cross sectional in design. Those factors most strongly and consistently associated with increased risk of developing poor mental health included students with experiences of trauma in childhood, those that identify as LGBTQ and students with autism. Factors that promote wellbeing include developing strong and supportive social networks. Students who are prepared and able to adjust to the changes that moving into higher education presents also experience better mental health. Some behaviours that are associated with poor mental health include lack of engagement both with learning and leisure activities and poor mental health literacy.

Improved knowledge of factors associated with poor mental health and also those that increase mental wellbeing can provide a foundation for designing strategies and specific interventions that can prevent poor mental health and ensuring targeted support is available for students at increased risk.

Peer Review reports

Poor mental health of students in further and higher education is an increasing concern for public health and policy [ 1 , 2 , 3 , 4 ]. A 2020 Insight Network survey of students from 10 universities suggests that “1 in 5 students has a current mental health diagnosis” and that “almost half have experienced a serious psychological issue for which they felt they needed professional help”—an increase from 1 in 3 in the same survey conducted in 2018 [ 5 ]. A review of 105 Further Education (FE) colleges in England found that over a three-year period, 85% of colleges reported an increase in mental health difficulties [ 1 ]. Depression and anxiety were both prevalent and widespread in students; all colleges reported students experiencing depression and 99% reported students experiencing severe anxiety [ 5 , 6 ]. A UK cohort study found that levels of psychological distress increase on entering university [ 7 ], and recent evidence suggests that the prevalence of mental health problems among university students, including self-harm and suicide, is rising, [ 3 , 4 ] with increases in demand for services to support student mental health and reports of some universities finding a doubling of the number of students accessing support [ 8 ]. These common mental health difficulties clearly present considerable threat to the mental health and wellbeing of students but their impact also has educational, social and economic consequences such as academic underperformance and increased risk of dropping out of university [ 9 , 10 ].

Policy changes may have had an influence on the student experience, and on the levels of mental health problems seen in the student population; the biggest change has arguably been the move to widen higher education participation and to enable a more diverse demographic to access University education. The trend for widening participation has been continually rising since the late 1960s [ 11 ] but gained impetus in the 2000s through the work of the Higher Education Funding Council for England (HEFCE). Macaskill (2013) [ 12 ] suggests that the increased access to higher education will have resulted in more students attending university from minority groups and less affluent backgrounds, meaning that more students may be vulnerable to mental health problems, and these students may also experience greater challenges in making the transition to higher education.

Another significant change has been the introduction of tuition fees in 1998, which required students to self fund up to £1,000 per academic year. Since then, tuition fees have increased significantly for many students. With the abolition of maintenance grants, around 96% of government support for students now comes in the form of student loans [ 13 ]. It is estimated that in 2017, UK students were graduating with average debts of £50,000, and this figure was even higher for the poorest students [ 13 ]. There is a clear association between a student’s mental health and financial well-being [ 14 ], with “increased financial concern being consistently associated with worse health” [ 15 ].

The extent to which the increase in poor mental health is also being seen amongst non-students of a similar age is not well understood and warrants further study. However, the increase in poor mental health specifically within students in higher education highlights a need to understand what the risk factors are and what might be done within these settings to ensure young people are learning and developing and transitioning into adulthood in environments that promote mental wellbeing.

Commencing higher education represents a key transition point in a young person’s life. It is a stage often accompanied by significant change combined with high expectations of high expectations from students of what university life will be like, and also high expectations from themselves and others around their own academic performance. Relevant factors include moving away from home, learning to live independently, developing new social networks, adjusting to new ways of learning, and now also dealing with the additional greater financial burdens that students now face.

The recent global COVID-19 pandemic has had considerable impact on mental health across society, and there is concern that younger people (ages 18–25) have been particularly affected. Data from Canada [ 16 ] indicate that among survey respondents, “almost two-thirds (64%) of those aged 15 to 24 reported a negative impact on their mental health, while just over one-third (35%) of those aged 65 and older reported a negative impact on their mental health since physical distancing began” (ibid, p.4). This suggests that older adults are more prepared for the kind of social isolation which has been brought about through the response to COVID-19, whereas young adults have found this more difficult to cope with. UK data from the National Union of Students reports that for over half of UK students, their mental health is worse than before the pandemic [ 17 ]. Before COVID-19, students were already reporting increasing levels of mental health problems [ 2 ], but the COVID-19 pandemic has added a layer of “chronic and unpredictable” stress, creating the perfect conditions for a mental health crisis [ 18 ]. An example of this is the referrals (both urgent and routine) of young people with eating disorders for treatment in the NHS which almost doubled in number from 2019 to 2020 [ 19 ]. The travel restrictions enforced during the pandemic have also impacted on student mental health, particularly for international students who may have been unable to commence studies or go home to see friends and family during holidays [ 20 ].

With the increasing awareness and concern in the higher education sector and national bodies regarding student mental health has come increasing focus on how to respond. Various guidelines and best practice have been developed, e.g. ‘Degrees of Disturbance’ [ 21 ], ‘Good Practice Guide on Responding to Student Mental Health Issues: Duty of Care Responsibilities for Student Services in Higher Education’ [ 22 ] and the recent ‘The University Mental Health Charter’ [ 2 ]. Universities UK produced a Good Practice Guide in 2015 called “Student mental wellbeing in higher education” [ 23 ]. An increasing number of initiatives have emerged that are either student-led or jointly developed with students, and which reflect the increasing emphasis students and student bodies place on mental health and well-being and the increased demand for mental health support: Examples include: Nightline— www.nightline.ac.uk , Students Against Depression— www.studentsagainstdepression.org , Student Minds— www.studentminds.org.uk/student-minds-and-mental-wealth.html and The Alliance for Student-Led Wellbeing— www.alliancestudentwellbeing.weebly.com/ .

Although requests for professional support have increased substantially [ 24 ] only a third of students with mental health problems seek support from counselling services in the UK [ 12 ]. Many students encounter barriers to seeking help such as stigma or lack of awareness of services [ 25 ], and without formal support or intervention, there is a risk of deterioration. FE colleges and universities have identified the need to move beyond traditional forms of support and provide alternative, more accessible interventions aimed at improving mental health and well-being. Higher education institutions have a unique opportunity to identify, prevent, and treat mental health problems because they provide support in multiple aspects of students’ lives including academic studies, recreational activities, pastoral and counselling services, and residential accommodation.

In order to develop services that better meet the needs of students and design environments that are supportive of developing mental wellbeing it is necessary to explore and better understand the factors that lead to poor mental health in students.

Research objectives

The overall aim of this review was to identify, appraise and synthesise existing research evidence that explores the aetiology of poor mental health and mental wellbeing amongst students in tertiary level education. We aimed to gain a better understanding of the mechanisms that lead to poor mental health amongst tertiary level students and, in so doing, make evidence-based recommendations for policy, practice and future research priorities. Specific objectives in line with the project brief were to:

To co-produce with stakeholders a conceptual framework for exploring the factors associated with poorer mental health in students in tertiary settings. The factors may be both predictive, identifying students at risk, or causal, explaining why they are at risk. They may also be protective, promoting mental wellbeing.

To conduct a review drawing on qualitative studies, observational studies and surveys to explore the aetiology of poor mental health in students in university and college settings and identify factors which promote mental wellbeing amongst students.

To identify evidence-based recommendations for policy, service provision and future research that focus on prevention and early identification of poor mental health

Methodology

Identification of relevant evidence.

The following inclusion criteria were used to guide the development of the search strategy and the selection of studies.

We included students from a variety of further education settings (16 yrs + or 18 yrs + , including mature students, international students, distance learning students, students at specific transition points).

Universities and colleges in the UK. We were also interested in the context prior to the beginning of tertiary education, including factors during transition from home and secondary education or existing employment to tertiary education.

Any factor shown to be associated with mental health of students in tertiary level education. This included clinical indicators such as diagnosis and treatment and/or referral for depression and anxiety. Self-reported measures of wellbeing, happiness, stress, anxiety and depression were included. We did not include measures of academic achievement or engagement with learning as indicators of mental wellbeing.

Study design

We included cross-sectional and longitudinal studies that looked at factors associated with mental health outcomes in Table 5 .

Data extraction and quality appraisal

We extracted and tabulated key data from the included papers. Data extraction was undertaken by one reviewer, with a 10% sample checked for accuracy and consistency The quality of the included studies were evaluated using the Newcastle-Ottawa Scale [ 26 ] and the findings of the quality appraisal used in weighting the strength of associations and also identifying gaps for future high quality research.

Involvement of stakeholders

We recruited students, ex-students and parents of students to a public involvement group which met on-line three times during the process of the review and following the completion of the review. During a workshop meeting we asked for members of the group to draw on their personal experiences to suggest factors which were not mentioned in the literature.

Methods of synthesis

We undertook a narrative synthesis [ 27 ] due to the heterogeneity in the exposures and outcomes that were measured across the studies. Data showing the direction of effects and the strength of the association (correlation coefficients) were recorded and tabulated to aid comparison between studies.

Search strategy

Searches were conducted in the following electronic databases: Medline, Applied Social Sciences Index and Abstracts (ASSIA), International Bibliography of Social Sciences (IBSS), Science,PsycINFO and Science and Social Sciences Ciatation Indexes. Additional searches of grey literature, and reference lists of included studies were also undertaken.

The search strategy combined a number of terms relating to students and mental health and risk factors. The search terms included both subject (MeSH) and free-text searches. The searches were limited to papers about humans in English, published from 2010 to June 2020. The flow of studies through the review process is summarised in Fig.  1 .

Flow diagram

The full search strategy for Medline is provided in Appendix 1 .

Thirty-one quantitative, observational studies (39 papers) met the inclusion criteria. The total number of students that participated in the quantitative studies was 17,476, with studies ranging in size from 57 to 3706. Eighteen studies recruited student participants from only one university; five studies (10 publications) [ 28 , 29 , 30 , 31 , 32 , 33 , 34 , 35 , 36 , 37 ] included seven or more universities. Six studies (7 publications) [ 35 , 36 , 37 , 38 , 39 , 40 , 41 ] only recruited first year students, while the majority of studies recruited students from a range of year groups. Five studies [ 39 , 42 , 43 , 44 , 45 ] recruited only, or mainly, psychology students which may impact on the generalisability of findings. A number of studies focused on students studying particular subjects including: nursing [ 46 ] medicine [ 47 ], business [ 48 ], sports science [ 49 ]. One study [ 50 ] recruited LGBTQ (lesbian, gay, bisexual, transgender, intersex, queer/questioning) students, and one [ 51 ] recruited students who had attended hospital having self-harmed. In 27 of the studies, there were more female than male participants. The mean age of the participants ranged from 19 to 28 years. Ethnicity was not reported in 19 of the studies. Where ethnicity was reported, the proportion that were ‘white British’ ranged from 71 – 90%. See Table 1 for a summary of the characteristics of the included studies and the participants.

Design and quality appraisal of the included studies

The majority of included studies ( n  = 22) were cross-sectional surveys. Nine studies (10 publications) [ 35 , 36 , 39 , 41 , 43 , 50 , 51 , 52 , 53 , 62 ] were longitudinal in design, recording survey data at different time points to explore changes in the variables being measured. The duration of time that these studies covered ranged from 19 weeks to 12 years. Most of the studies ( n  = 22) only recruited participants from a single university. The use of one university setting and the large number of studies that recruited only psychology students weakens the wider applicability of the included studies.

Quantitative variables

Included studies ( n  = 31) measured a wide range of variables and explored their association with poor mental health and wellbeing. These included individual level factors: age, gender, sexual orientation, ethnicity and a range of psychological variables. They also included factors that related to mental health variables (family history, personal history and mental health literacy), pre-university factors (childhood trauma and parenting behaviour. University level factors including social isolation, adjustment and engagement with learning. Their association was measured against different measures of positive mental health and poor mental health.

Measurement of association and the strength of that association has some limitations in addressing our research question. It cannot prove causality, and nor can it capture fully the complexity of the inter-relationship and compounding aspect of the variables. For example, the stress of adjustment may be manageable, until it is combined with feeling isolated and out of place. Measurement itself may also be misleading, only capturing what is measureable, and may miss variables that are important but not known. We included both qualitative and PPI input to identify missed but important variables.

The wide range of variables and different outcomes, with few studies measuring the same variable and outcomes, prevented meta-analyses of findings which are therefore described narratively.

The variables described were categorised during the analyses into the following categories:

Vulnerabilities – factors that are associated with poor mental health

Individual level factors including; age, ethnicity, gender and a range of psychological variables were all measured against different mental health outcomes including depression, anxiety, paranoia, and suicidal behaviour, self-harm, coping and emotional intelligence.

Six studies [ 40 , 42 , 47 , 50 , 60 , 63 ] examined a student’s ages and association with mental health. There was inconsistency in the study findings, with studies finding that age (21 or older) was associated with fewer depressive symptoms, lower likelihood of suicide ideation and attempt, self-harm, and positively associated with better coping skills and mental wellbeing. This finding was not however consistent across studies and the association was weak. Theoretical models that seek to explain this mechanism have suggested that older age groups may cope better due to emotion-regulation strategies improving with age [ 67 ]. However, those over 30 experienced greater financial stress than those aged 17-19 in another study [ 63 ].

Sexual orientation

Four studies [ 33 , 40 , 64 , 68 ] examined the association between poor mental health and sexual orientation status. In all of the studies LGBTQ students were at significantly greater risk of mental health problems including depression [ 40 ], anxiety [ 40 ], suicidal behaviour [ 33 , 40 , 64 ], self harm [ 33 , 40 , 64 ], use of mental health services [ 33 ] and low levels of wellbeing [ 68 ]. The risk of mental health problems in these students compared with heterosexual students, ranged from OR 1.4 to 4.5. This elevated risk may reflect the greater levels of isolation and discrimination commonly experienced by minority groups.

Nine studies [ 33 , 38 , 39 , 40 , 42 , 47 , 50 , 60 , 63 ] examined whether gender was associated mental health variables. Two studies [ 33 , 47 ] found that being female was statistically significantly associated with use of mental health services, having a current mental health problem, suicide risk, self harm [ 33 ] and depression [ 47 ]. The results were not consistent, with another study [ 60 ] finding the association was not significant. Three studies [ 39 , 40 , 42 ] that considered mediating variables such as adaptability and coping found no difference or very weak associations.

Two studies [ 47 , 60 ] examined the extent to which ethnicity was associated with mental health One study [ 47 ] reported that the risks of depression were significantly greater for those who categorised themselves as non-white (OR 8.36 p = 0.004). Non-white ethnicity was also associated with poorer mental health in another cross-sectional study [ 63 ]. There was no significant difference in the McIntyre et al. (2018) study [ 60 ]. The small number of participants from ethnic minority groups represented across the studies means that this data is very limited.

Family factors

Six studies [ 33 , 40 , 42 , 50 , 60 ] explored the association of a concept that related to a student’s experiences in childhood and before going to university. Three studies [ 40 , 50 , 60 ] explored the impact of ACEs (Adverse Childhood Experiences) assessed using the same scale by Feletti (2009) [ 69 ] and another explored the impact of abuse in childhood [ 46 ]. Two studies examined the impact of attachment anxiety and avoidance [ 42 ], and parental acceptance [ 46 , 59 ]. The studies measured different mental health outcomes including; positive and negative affect, coping, suicide risk, suicide attempt, current mental health problem, use of mental health services, psychological adjustment, depression and anxiety.

The three studies that explored the impact of ACE’s all found a significant and positive relationship with poor mental health amongst university students. O’Neill et al. (2018) [ 50 ] in a longitudinal study ( n  = 739) showed that there was in increased likelihood in self-harm and suicidal behaviours in those with either moderate or high levels of childhood adversities (OR:5.5 to 8.6) [ 50 ]. McIntyre et al. (2018) [ 60 ] ( n  = 1135) also explored other dimensions of adversity including childhood trauma through multiple regression analysis with other predictive variables. They found that childhood trauma was significantly positively correlated with anxiety, depression and paranoia (ß = 0.18, 0.09, 0.18) though the association was not as strong as the correlation seen for loneliness (ß = 0.40) [ 60 ]. McLafferty et al. (2019) [ 40 ] explored the compounding impact of childhood adversity and negative parenting practices (over-control, overprotection and overindulgence) on poor mental health (depression OR 1.8, anxiety OR 2.1 suicidal behaviour OR 2.3, self-harm OR 2.0).

Gaan et al.’s (2019) survey of LGBTQ students ( n  = 1567) found in a multivariate analyses that sexual abuse, other abuse from violence from someone close, and being female had the highest odds ratios for poor mental health and were significantly associated with all poor mental health outcomes [ 33 ].

While childhood trauma and past abuse poses a risk to mental health for all young people it may place additional stresses for students at university. Entry to university represents life stage where there is potential exposure to new and additional stressors, and the possibility that these students may become more isolated and find it more difficult to develop a sense of belonging. Students may be separated for the first time from protective friendships. However, the mechanisms that link childhood adversities and negative psychopathology, self-harm and suicidal behaviour are not clear [ 40 ]. McLafferty et al. (2019) also measured the ability to cope and these are not always impacted by childhood adversities [ 40 ]. They suggest that some children learn to cope and build resilience that may be beneficial.

McLafferty et al. (2019) [ 40 ] also studied parenting practices. Parental over-control and over-indulgence was also related to significantly poorer coping (OR -0.075 p  < 0.05) and this was related to developing poorer coping scores (OR -0.21 p  < 0.001) [ 40 ]. These parenting factors only became risk factors when stress levels were high for students at university. It should be noted that these studies used self-report, and responses regarding views of parenting may be subjective and open to interpretation. Lloyd et al.’s (2014) survey found significant positive correlations between perceived parental acceptance and students’ psychological adjustment, with paternal acceptance being the stronger predictor of adjustment.

Autistic students may display social communication and interaction deficits that can have negative emotional impacts. This may be particularly true during young adulthood, a period of increased social demands and expectations. Two studies [ 56 ] found that those with autism had a low but statistically significant association with poor social problem-solving skills and depression.

Mental health history

Three studies [ 47 , 51 , 68 ] investigated mental health variables and their impact on mental health of students in higher education. These included; a family history of mental illness and a personal history of mental illness.

Students with a family history or a personal history of mental illness appear to have a significantly greater risk of developing problems with mental health at university [ 47 ]. Mahadevan et al. (2010) [ 51 ] found that university students who self-harm have a significantly greater risk (OR 5.33) of having an eating disorder than a comparison group of young adults who self-harm but are not students.

Buffers – factors that are protective of mental wellbeing

Psychological factors.

Twelve studies [ 29 , 39 , 40 , 41 , 42 , 43 , 46 , 49 , 54 , 58 , 64 ] assessed the association of a range of psychological variables and different aspects of mental wellbeing and poor mental health. We categorised these into the following two categories: firstly, psychological variables measuring an individual’s response to change and stressors including adaptability, resilience, grit and emotional regulation [ 39 , 40 , 41 , 42 , 43 , 46 , 49 , 54 , 58 ] and secondly, those that measure self-esteem and body image [ 29 , 64 ].

The evidence from the eight included quantitative studies suggests that students with psychological strengths including; optimism, self-efficacy [ 70 ], resilience, grit [ 58 ], use of positive reappraisal [ 49 ], helpful coping strategies [ 42 ] and emotional intelligence [ 41 , 46 ] are more likely to experience greater mental wellbeing (see Table 2 for a description of the psychological variables measured). The positive association between these psychological strengths and mental well-being had a positive affect with associations ranging from r  = 0.2–0.5 and OR1.27 [ 41 , 43 , 46 , 49 , 54 ] (low to moderate strength of association). The negative associations with depressive symptoms are also statistically significant but with a weaker association ( r  = -0.2—0.3) [ 43 , 49 , 54 ].

Denovan (2017a) [ 43 ] in a longitudinal study found that the association between psychological strengths and positive mental wellbeing was not static and that not all the strengths remained statistically significant over time. The only factors that remained significant during the transition period were self-efficacy and optimism, remaining statistically significant as they started university and 6 months later.

Parental factors

Only one study [ 59 ] explored family factors associated with the development of psychological strengths that would equip young people as they managed the challenges and stressors encountered during the transition to higher education. Lloyd et al. (2014) [ 59 ] found that perceived maternal and paternal acceptance made significant and unique contributions to students’ psychological adjustment. Their research methods are limited by their reliance on retrospective measures and self-report measures of variables, and these results could be influenced by recall bias.

Two studies [ 29 , 64 ] considered the impact of how individuals view themselves on poor mental health. One study considered the impact of self-esteem and the association with non-accidental self-injury (NSSI) and suicide attempt amongst 734 university students. As rates of suicide and NSSI are higher amongst LGBT (lesbian, gay, bisexual, transgender) students, the prevalence of low self-esteem was compared. There was a low but statistically significant association between low self-esteem and NSSI, though not for suicide attempt. A large survey, including participants from seven universities [ 42 ] compared depressive symptoms in students with marked body image concerns, reporting that the risk of depressive symptoms was greater (OR 2.93) than for those with lower levels of body image concerns.

Mental health literacy and help seeking behaviour

Two studies [ 48 , 68 ] investigated attitudes to mental illness, mental health literacy and help seeking for mental health problems.

University students who lack sufficient mental health literacy skills to be able to recognise problems or where there are attitudes that foster shame at admitting to having mental health problems can result in students not recognising problems and/or failing to seek professional help [ 48 , 68 ]. Gorcyznski et al. (2017) [ 68 ] found that women and those who had a history of previous mental health problems exhibited significantly higher levels of mental health literacy. Greater mental health literacy was associated with an increased likelihood that individuals would seek help for mental health problems. They found that many students find it hard to identify symptoms of mental health problems and that 42% of students are unaware of where to access available resources. Of those who expressed an intention to seek help for mental health problems, most expressed a preference for online resources, and seeking help from family and friends, rather than medical professionals such as GPs.

Kotera et al. (2019) [ 48 ] identified self-compassion as an explanatory variable, reducing social comparison, promoting self-acceptance and recognition that discomfort is an inevitable human experience. The study found a strong, significant correlation between self-compassion and mental health symptoms ( r  = -0.6. p  < 0.01).

There again appears to be a cycle of reinforcement, where poor mental health symptoms are felt to be a source of shame and become hidden, help is not sought, and further isolation ensues, leading to further deterioration in mental health. Factors that can interrupt the cycle are self-compassion, leading to more readiness to seek help (see Fig.  2 ).

Poor mental health – cycles of reinforcement

Social networks

Nine studies [ 33 , 38 , 41 , 46 , 51 , 54 , 60 , 64 , 65 ] examined the concepts of loneliness and social support and its association with mental health in university students. One study also included students at other Higher Education Institutions [ 46 ]. Eight of the studies were surveys, and one was a retrospective case control study to examine the differences between university students and age-matched young people (non-university students) who attended hospital following deliberate self-harm [ 51 ].

Included studies demonstrated considerable variation in how they measured the concepts of social isolation, loneliness, social support and a sense of belonging. There were also differences in the types of outcomes measured to assess mental wellbeing and poor mental health. Grouping the studies within a broad category of ‘social factors’ therefore represents a limitation of this review given that different aspects of the phenomena may have been being measured. The tools used to measure these variables also differed. Only one scale (The UCLA loneliness scale) was used across multiple studies [ 41 , 60 , 65 ]. Diverse mental health outcomes were measured across the studies including positive affect, flourishing, self-harm, suicide risk, depression, anxiety and paranoia.

Three studies [ 41 , 60 , 62 ] measuring loneliness, two longitudinally [ 41 , 62 ], found a consistently positive association between loneliness and poor mental health in university students. Greater loneliness was linked to greater anxiety, stress, depression, poor general mental health, paranoia, alcohol abuse and eating disorder problems. The strength of the correlations ranged from 0–3-0.4 and were all statistically significant (see Tables 3 and 4 ). Loneliness was the strongest overall predictor of mental distress, of those measured. A strong identification with university friendship groups was most protective against distress relative to other social identities [ 60 ]. Whether poor mental health is the cause, or the result of loneliness was explored further in the studies. The results suggest that for general mental health, stress, depression and anxiety, loneliness induces or exacerbates symptoms of poor mental health over time [ 60 , 62 ]. The feedback cycle is evident, with loneliness leading to poor mental health which leads to withdrawal from social contacts and further exacerbation of loneliness.

Factors associated with protecting against loneliness by fostering supportive friendships and promoting mental wellbeing were also identified. Beliefs about the value of ‘leisure coping’, and attributes of resilience and emotional intelligence had a moderate, positive and significant association with developing mental wellbeing and were explored in three studies [ 46 , 54 , 66 ].

The transition to and first year at university represent critical times when friendships are developed. Thomas et al. (2020) [ 65 ] explored the factors that predict loneliness in the first year of university. A sense of community and higher levels of ‘social capital’ were significantly associated with lower levels of loneliness. ‘Social capital’ scales measure the development of emotionally supportive friendships and the ability to adjust to the disruption of old friendships as students transition to university. Students able to form close relationships within their first year at university are less likely to experience loneliness (r-0.09, r- 0.36, r- 0.34). One study [ 38 ] investigating the relationship between student experience and being the first in the family to attend university found that these students had lower ratings for peer group interactions.

Young adults at university and in higher education are facing multiple adjustments. Their ability to cope with these is influenced by many factors. Supportive friendships and a sense of belonging are factors that strengthen coping. Nightingale et al. (2012) undertook a longitudinal study to explore what factors were associated with university adjustment in a sample of first year students ( n  = 331) [ 41 ]. They found that higher skills of emotion management and emotional self-efficacy were predictive of stable adjustment. These students also reported the lowest levels of loneliness and depression. This group had the skills to recognise their emotions and cope with stressors and were confident to access support. Students with poor emotion management and low levels of emotional self-efficacy may benefit from intervention to support the development of adaptive coping strategies and seeking support.

The positive and negative feedback loops

The relationship between the variables described appeared to work in positive and negative feedback loops with high levels of social capital easing the formation of a social network which acts as a critical buffer to stressors (see Fig.  3 ). Social networks and support give further strengthening and reinforcement, stimulating positive affect, engagement and flourishing. These, in turn, widen and deepen social networks for support and enhance a sense of wellbeing. Conversely young people who enter the transition to university/higher education with less social capital are less likely to identify with and locate a social network; isolation may follow, along with loneliness, anxiety, further withdrawal from contact with social networks and learning, and depression.

Triggers – factors that may act in combination with other factors to lead to poor mental health

Stress is seen as playing a key role in the development of poor mental health for students in higher education. Theoretical models and empirical studies have suggested that increases in stress are associated with decreases in student mental health [ 12 , 43 ]. Students at university experience the well-recognised stressors associated with academic study such as exams and course work. However, perhaps less well recognised are the processes of transition, requiring adapting to a new social and academic environment (Fisher 1994 cited by Denovan 2017a) [ 43 ]. Por et al. (2011) [ 46 ] in a small ( n  = 130 prospective survey found a statistically significant correlation between higher levels of emotional intelligence and lower levels of perceived stress ( r  = 0.40). Higher perceived stress was also associated with negative affect in two studies [ 43 , 46 ], and strongly negatively associated with positive affect (correlation -0.62) [ 54 ].

University variables

Eleven studies [ 35 , 39 , 47 , 51 , 52 , 54 , 60 , 63 , 65 , 83 , 84 ] explored university variables, and their association with mental health outcomes. The range of factors and their impact on mental health variables is limited, and there is little overlap. Knowledge gaps are shown by factors highlighted by our PPI group as potentially important but not identified in the literature (see Table 5 ). It should be noted that these may reflect the focus of our review, and our exclusion of intervention studies which may evaluate university factors.

High levels of perceived stress caused by exam and course work pressure was positively associated with poor mental health and lack of wellbeing [ 51 , 52 , 54 ]. Other potential stressors including financial anxieties and accommodation factors appeared to be less consistently associated with mental health outcomes [ 35 , 38 , 47 , 51 , 60 , 62 ]. Important mediators and buffers to these stressors are coping strategies and supportive networks (see conceptual model Appendix 2 ). One impact of financial pressures was that students who worked longer hours had less interaction with their peers, limiting the opportunities for these students to benefit from the protective effects of social support.

Red flags – behaviours associated with poor mental health and/or wellbeing

Engagement with learning and leisure activities.

Engagement with learning activities was strongly and positively associated with characteristics of adaptability [ 39 ] and also happiness and wellbeing [ 52 ] (see Fig.  4 ). Boulton et al. (2019) [ 52 ] undertook a longitudinal survey of undergraduate students at a campus-based university. They found that engagement and wellbeing varied during the term but were strongly correlated.

Engagement and wellbeing

Engagement occurred in a wide range of activities and behaviours. The authors suggest that the strong correlation between all forms of engagement with learning has possible instrumental value for the design of systems to monitor student engagement. Monitoring engagement might be used to identify changes in the behaviour of individuals to assist tutors in providing support and pastoral care. Students also were found to benefit from good induction activities provided by the university. Greater induction satisfaction was positively and strongly associated with a sense of community at university and with lower levels of loneliness [ 65 ].

The inte r- related nature of these variables is depicted in Fig.  4 . Greater adaptability is strongly associated with more positive engagement in learning and university life. More engagement is associated with higher mental wellbeing.

Denovan et al. (2017b) [ 54 ] explored leisure coping, its psychosocial functions and its relationship with mental wellbeing. An individual’s beliefs about the benefits of leisure activities to manage stress, facilitate the development of companionship and enhance mood were positively associated with flourishing and were negatively associated with perceived stress. Resilience was also measured. Resilience was strongly and positively associated with leisure coping beliefs and with indicators of mental wellbeing. The authors conclude that resilient individuals are more likely to use constructive means of coping (such as leisure coping) to proactively cultivate positive emotions which counteract the experience of stress and promote wellbeing. Leisure coping is predictive of positive affect which provides a strategy to reduce stress and sustain coping. The belief that friendships acquired through leisure provide social support is an example of leisure coping belief. Strong emotionally attached friendships that develop through participation in shared leisure pursuits are predictive of higher levels of well-being. Friendship bonds formed with fellow students at university are particularly important for maintaining mental health, and opportunities need to be developed and supported to ensure that meaningful social connections are made.

The ‘broaden-and-build theory’ (Fredickson 2004 [ 85 ] cited by [ 54 ]) may offer an explanation for the association seen between resilience, leisure coping and psychological wellbeing. The theory is based upon the role that positive and negative emotions have in shaping human adaptation. Positive emotions broaden thinking, enabling the individual to consider a range of ways of dealing with and adapting to their environment. Conversely, negative emotions narrow thinking and limit options for adapting. The former facilitates flourishing, facilitating future wellbeing. Resilient individuals are more likely to use constructive means of coping which generate positive emotion (Tugade & Fredrickson 2004 [ 86 ], cited by [ 54 ]). Positive emotions therefore lead to growth in coping resources, leading to greater well-being.

Health behaviours at university

Seven studies [ 29 , 31 , 38 , 45 , 51 , 54 , 66 ] examined how lifestyle behaviours might be linked with mental health outcomes. The studies looked at leisure activities [ 63 , 80 ], diet [ 29 ], alcohol use [ 29 , 31 , 38 , 51 ] and sleep [ 45 ].

Depressive symptoms were independently associated with problem drinking and possible alcohol dependence for both genders but were not associated with frequency of drinking and heavy episodic drinking. Students with higher levels of depressive symptoms reported significantly more problem drinking and possible alcohol dependence [ 31 ]. Mahadevan et al. (2010) [ 51 ] compared students and non-students seen in hospital for self-harm and found no difference in harmful use of alcohol and illicit drugs.

Poor sleep quality and increased consumption of unhealthy foods were also positively associated with depressive symptoms and perceived stress [ 29 ]. The correlation with dietary behaviours and poor mental health outcomes was low, but also confirmed by the negative correlation between less perceived stress and depressive symptoms and consumption of a healthier diet.

Physical activity and participation in leisure pursuits were both strongly correlated with mental wellbeing ( r  = 0.4) [ 54 ], and negatively correlated with depressive symptoms and anxiety ( r  = -0.6, -0.7) [ 66 ].

Thirty studies measuring the association between a wide range of factors and poor mental health and mental wellbeing in university and college students were identified and included in this review. Our purpose was to identify the factors that contribute to the growing prevalence of poor mental health amongst students in tertiary level education within the UK. We also aimed to identify factors that promote mental wellbeing and protect against deteriorating poor mental health.

Loneliness and social isolation were strongly associated with poor mental health and a sense of belonging and a strong support network were strongly associated with mental wellbeing and happiness. These associations were strongly positive in the eight studies that explored them and are consistent with other meta-analyses exploring the link between social support and mental health [ 87 ].

Another factor that appeared to be protective was older age when starting university. A wide range of personal traits and characteristics were also explored. Those associated with resilience, ability to adjust and better coping led to improved mental wellbeing. Better engagement appeared as an important mediator to potentially explain the relationship between these two variables. Engagement led to students being able to then tap into those features that are protective and promoting of mental wellbeing.

Other important risk factors for poor mental wellbeing that emerged were those students with existing or previous mental illness. Students on the autism spectrum and those with poor social problem-solving also were more likely to suffer from poor mental health. Negative self-image was also associated with poor mental health at university. Eating disorders were strongly associated with poor mental wellbeing and were found to be far more of a risk in students at university than in a comparative group of young people not in higher education. Other studies of university students also found that pre-existing poor mental health was a strong predictor of poor mental health in university students [ 88 ].

At a family level, the experience of childhood trauma and adverse experiences including, for example, neglect, household dysfunction or abuse, were strongly associated with poor mental health in young people at university. Students with a greater number of ‘adverse childhood experiences’ were at significantly greater risk of poor mental health than those students without experience of childhood trauma. This was also identified in a review of factors associated with depression and suicide related outcomes amongst university undergraduate students [ 88 ].

Our findings, in contrast to findings from other studies of university students, did not find that female gender associated with poor mental health and wellbeing, and it also found that being a mature student was protective of mental wellbeing.

Exam and course work pressure was associated with perceived stress and poor mental health. A lack of engagement with learning activities was also associated with poor mental health. A number of variables were not consistently shown to be associated with poor mental health including financial concerns and accommodation factors. Very little evidence related to university organisation or support structures was assessed in the evidence. One study found that a good induction programme had benefits for student mental wellbeing and may be a factor that enables students to become a part of a social network positive reinforcement cycle. Involvement in leisure activities was also found to be associated with improved coping strategies and better mental wellbeing. Students with poorer mental health tended to also eat in a less healthy manner, consume more harmful levels of alcohol, and experience poorer sleep.

This evidence review of the factors that influence mental health and wellbeing indicate areas where universities and higher education settings could develop and evaluate innovations in practice. These include:

Interventions before university to improve preparation of young people and their families for the transition to university.

Exploratory work to identify the acceptability and feasibility of identifying students at risk or who many be exhibiting indications of deteriorating mental health

Interventions that set out to foster a sense of belonging and identify

Creating environments that are helpful for building social networks

Improving mental health literacy and access to high quality support services

This review has a number of limitations. Most of the included studies were cross-sectional in design, with a small number being longitudinal ( n  = 7), following students over a period of time to observe changes in the outcomes being measured. Two limitations of these sources of data is that they help to understand associations but do not reveal causality; secondly, we can only report the findings for those variables that were measured, and we therefore have to support causation in assuming these are the only factors that are related to mental health.

Furthermore, our approach has segregated and categorised variables in order to better understand the extent to which they impact mental health. This approach does not sufficiently explore or reveal the extent to which variables may compound one another, for example, feeling the stress of new ways of learning may not be a factor that influences mental health until it is combined with a sense of loneliness, anxiety about financial debt and a lack of parental support. We have used our PPI group and the development of vignettes of their experiences to seek to illustrate the compounding nature of the variables identified.

We limited our inclusion criteria to studies undertaken in the UK and published within the last decade (2009–2020), again meaning we may have limited our inclusion of relevant data. We also undertook single data extraction of data which may increase the risk of error in our data.

Understanding factors that influence students’ mental health and wellbeing offers the potential to find ways to identify strategies that enhance the students’ abilities to cope with the challenges of higher education. This review revealed a wide range of variables and the mechanisms that may explain how they impact upon mental wellbeing and increase the risk of poor mental health amongst students. It also identified a need for interventions that are implemented before young people make the transition to higher education. We both identified young people who are particularly vulnerable and the factors that arise that exacerbate poor mental health. We highlight that a sense of belonging and supportive networks are important buffers and that there are indicators including lack of engagement that may enable early intervention to provide targeted and appropriate support.

Availability of data and materials

Further details of the study and the findings can be provided on request to the lead author ([email protected]).

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Acknowledgements

We acknowledge the input from our public advisory group which included current and former students, and family members of students who have struggled with their mental health. The group gave us their extremely valuable insights to assist our understanding of the evidence.

This project was supported by funding from the National Institute for Health Research as part of the NIHR Public Health Research  Programme (fuding reference 127659 Public Health Review Team). The views expressed are those of the authors and not necessarily those of the NIHR or the Department of Health and Social Care.

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All of the included authors designed the project methods and prepared a protocol. A.C. designed the search strategy. F.C, L.B and C.B screened the identified citations and undertook data extraction. S.B. led the PPI involvement. JD participated as a member of the PPI group. F.C and L.B undertook the analysis. F.C. and L.B wrote the main manuscript text. All authors reviewed the manuscript. F.C designed Figs. 2 , 3 and 4 . The author(s) read and approved the final manuscript.

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Campbell, F., Blank, L., Cantrell, A. et al. Factors that influence mental health of university and college students in the UK: a systematic review. BMC Public Health 22 , 1778 (2022). https://doi.org/10.1186/s12889-022-13943-x

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Study Tracks Shifts in Student Mental Health During College

Dartmouth study followed 200 students all four years, including through the pandemic.

Phone App Uses AI to Detect Depression From Facial Cues

A four-year study by Dartmouth researchers captures the most in-depth data yet on how college students’ self-esteem and mental health fluctuates during their four years in academia, identifying key populations and stressors that the researchers say administrators could target to improve student well-being. 

The study also provides among the first real-time accounts of how the coronavirus pandemic affected students’ behavior and mental health. The stress and uncertainty of COVID-19 resulted in long-lasting behavioral changes that persisted as a “new normal” even as the pandemic diminished, including students feeling more stressed, less socially engaged, and sleeping more.

The researchers tracked more than 200 Dartmouth undergraduates in the classes of 2021 and 2022 for all four years of college. Students volunteered to let a specially developed app called StudentLife tap into the sensors that are built into smartphones. The app cataloged their daily physical and social activity, how long they slept, their location and travel, the time they spent on their phone, and how often they listened to music or watched videos. Students also filled out weekly behavioral surveys, and selected students gave post-study interviews. 

The study—which is the longest mobile-sensing study ever conducted—is published in the Proceedings of the ACM on Interactive, Mobile, Wearable and Ubiquitous Technologies .

The researchers will present it at the Association of Computing Machinery’s UbiComp/ISWC 2024 conference in Melbourne, Australia, in October. 

These sorts of tools will have a tremendous impact on projecting forward and developing much more data-driven ways to intervene and respond exactly when students need it most.

The team made their anonymized data set publicly available —including self-reports, surveys, and phone-sensing and brain-imaging data—to help advance research into the mental health of students during their college years. 

Andrew Campbell , the paper’s senior author and Dartmouth’s Albert Bradley 1915 Third Century Professor of Computer Science, says that the study’s extensive data reinforces the importance of college and university administrators across the country being more attuned to how and when students’ mental well-being changes during the school year.

“For the first time, we’ve produced granular data about the ebb and flow of student mental health. It’s incredibly dynamic—there’s nothing that’s steady state through the term, let alone through the year,” he says. “These sorts of tools will have a tremendous impact on projecting forward and developing much more data-driven ways to intervene and respond exactly when students need it most.”

First-year and female students are especially at risk for high anxiety and low self-esteem, the study finds. Among first-year students, self-esteem dropped to its lowest point in the first weeks of their transition from high school to college but rose steadily every semester until it was about 10% higher by graduation.

“We can see that students came out of high school with a certain level of self-esteem that dropped off to the lowest point of the four years. Some said they started to experience ‘imposter syndrome’ from being around other high-performing students,” Campbell says. “As the years progress, though, we can draw a straight line from low to high as their self-esteem improves. I think we would see a similar trend class over class. To me, that’s a very positive thing.”

Female students—who made up 60% of study participants—experienced on average 5% greater stress levels and 10% lower self-esteem than male students. More significantly, the data show that female students tended to be less active, with male students walking 37% more often.

Sophomores were 40% more socially active compared to their first year, the researchers report. But these students also reported feeling 13% more stressed during their second year than during their first year as their workload increased, they felt pressure to socialize, or as first-year social groups dispersed.

One student in a sorority recalled that having pre-arranged activities “kind of adds stress as I feel like I should be having fun because everyone tells me that it is fun.” Another student noted that after the first year, “students have more access to the whole campus and that is when you start feeling excluded from things.” 

In a novel finding, the researchers identify an “anticipatory stress spike” of 17% experienced in the last two weeks of summer break. While still lower than mid-academic year stress, the spike was consistent across different summers.

In post-study interviews, some students pointed to returning to campus early for team sports as a source of stress. Others specified reconnecting with family and high school friends during their first summer home, saying they felt “a sense of leaving behind the comfort and familiarity of these long-standing friendships” as the break ended, the researchers report. 

“This is a foundational study,” says Subigya Nepal , first author of the study and a PhD candidate in Campbell’s research group. “It has more real-time granular data than anything we or anyone else has provided before. We don’t know yet how it will translate to campuses nationwide, but it can be a template for getting the conversation going.”

The depth and accuracy of the study data suggest that mobile-sensing software could eventually give universities the ability to create proactive mental-health policies specific to certain student populations and times of year, Campbell says.

For example, a paper Campbell’s research group published in 2022 based on StudentLife data showed that first-generation students experienced lower self-esteem and higher levels of depression than other students throughout their four years of college.

“We will be able to look at campus in much more nuanced ways than waiting for the results of an annual mental health study and then developing policy,” Campbell says. “We know that Dartmouth is a small and very tight-knit campus community. But if we applied these same methods to a college with similar attributes, I believe we would find very similar trends.”

Weathering the pandemic

When students returned home at the start of the coronavirus pandemic, the researchers found that self-esteem actually increased during the pandemic by 5% overall and by another 6% afterward when life returned closer to what it was before. One student suggested in their interview that getting older came with more confidence. Others indicated that being home led to them spending more time with friends talking on the phone, on social media, or streaming movies together. 

The data show that phone usage—measured by the duration a phone was unlocked—indeed increased by nearly 33 minutes, or 19%, during the pandemic, while time spent in physical activity dropped by 52 minutes, or 27%. By 2022, phone usage fell from its pandemic peak to just above pre-pandemic levels, while engagement in physical activity had recovered to exceed the pre-pandemic period by three minutes. 

Despite reporting higher self-esteem, students’ feelings of stress increased by more than 10% during the pandemic. By the end of the study in June 2022, stress had fallen by less than 2% of its pandemic peak, indicating that the experience had a lasting impact on student well-being, the researchers report. 

In early 2021, as students returned to campus, their reunion with friends and community was tempered by an overwhelming concern about the still-rampant coronavirus. “There was the first outbreak in winter 2021 and that was terrifying,” one student recalls. Another student adds: “You could be put into isolation for a long time even if you did not have COVID. Everyone was afraid to contact-trace anyone else in case they got mad at each other.”

Female students were especially concerned about the coronavirus, on average 13% more than male students. “Even though the girls might have been hanging out with each other more, they are more aware of the impact,” one female student reported. “I actually had COVID and exposed some friends of mine. All the girls that I told tested as they were worried. They were continually checking up to make sure that they did not have it and take it home to their family.”

Students still learning remotely had social levels 16% higher than students on campus, who engaged in activity an average of 10% less often than when they were learning from home. However, on-campus students used their phones 47% more often. When interviewed after the study, these students reported spending extended periods of time video-calling or streaming movies with friends and family.

Social activity and engagement had not yet returned to pre-pandemic levels by the end of the study in June 2022, recovering by a little less than 3% after a nearly 10% drop during the pandemic. Similarly, the pandemic correlates with students sticking closer to home, with their distance traveled nearly cut in half during the pandemic and holding at that level since then.

Campbell and several of his fellow researchers are now developing a smartphone app known as MoodCapture that uses artificial intelligence paired with facial-image processing software to reliably detect the onset of depression before the user even knows something is wrong.

Morgan Kelly can be reached at [email protected] .

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University students’ use of mental health services: a systematic review and meta-analysis

• T. G. Osborn 1 ,
• R. Saunders 1 , 2 &
• P. Fonagy 1  

International Journal of Mental Health Systems volume  16 , Article number:  57 ( 2022 ) Cite this article

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International estimates suggest around a third of students arrives at university with symptoms indicative of a common mental disorder, many in late adolescence at a developmentally high-risk period for the emergence of mental disorder. Universities, as settings, represent an opportunity to contribute to the improvement of population mental health. We sought to understand what is known about the management of student mental health, and asked: (1) What proportion of students use mental health services when experiencing psychological distress? (2) Does use by students differ across health service types?

A systematic review was conducted following PRISMA guidelines using a Context, Condition, Population framework (CoCoPop) with a protocol preregistered on Prospero (CRD42021238273). Electronic database searches in Medline, Embase, PsycINFO, ERIC and CINAHL Plus, key authors were contacted, citation searches were conducted, and the reference list of the WHO World Mental Health International College Student Initiative (WMH-ICS) was searched. Data extraction was performed using a pre-defined framework, and quality appraisal using the Joanna Briggs Institute tool. Data were synthesised narratively and meta-analyses at both the study and estimate level.

7789 records were identified through the search strategies, with a total of 44 studies meeting inclusion criteria. The majority of included studies from the USA (n = 36), with remaining studies from Bangladesh, Brazil, Canada, China, Ethiopia and Italy. Overall, studies contained 123 estimates of mental health service use associated with a heterogeneous range of services, taking highly variable numbers of students across a variety of settings.

This is the first systematic quantitative survey of student mental health service use. The empirical literature to date is very limited in terms of a small number of international studies outside of the USA; studies of how services link together, and of student access. The significant variation we found in the proportions of students using services within and between studies across different settings and populations suggests the current services described in the literature are not meeting the needs of all students.

Globally, university students could be considered a privileged group given the significant variation in percentage of national populations with a university education [ 1 ]. However, for those who do attend university usually do so at a developmentally high risk period for the emergence of mental heath problems [ 2 , 3 ]. Psychological distress, encompassing symptoms ranging from normal fluctuations in mood to the emergence of a serious mental illness, is an increasingly common experience among university students which can have significant consequences for individuals [ 4 , 5 ]. Recent international evidence suggests 35% of first year students report symptoms indicative of lifetime mental disorder, and 31.4% report symptoms in the previous 12 months [ 6 ]. International longitudinal research is more limited. Studies in Norway, the UK and the USA has shown both psychological distress and common mental disorders (CMD) have increased in prevalence among both students and similar aged non-student populations over the last 10 years [ 7 , 8 , 9 , 10 , 11 ]. Suicidal behaviour, while lower in students compared to matched non-student populations, has also increased over a similar timeframe in England and Wales [ 12 ]. International estimates among students suggest around 4.3% have attempted suicide in their lifetime [ 6 ]. The short- and longer-term consequences of mental health difficulties can be significant including poorer academic performance, relationship breakdown, and exclusion from the labour market [ 6 , 13 , 14 ]. Current students face greater financial and academic pressures compared to 20 years ago, which may be contributing to poorer mental health outcomes [ 2 , 15 , 16 , 17 ]. These findings suggest a significant mental health need among this population. [ 1 ].

For students in mental distress, the support available to them is likely to vary signficiantly between and within countries. For example, in many high-income countries (HIC) students may have a range of effective mental health services available to them but these services are often fragmented, uncoordinated and underutilised [ 6 , 19 , 20 ]. For example, US studies suggest around a 1/3 of students received treatment [ 9 ], while epidemiological studies suggest this varies widely independent of need based on sex and gender, ethnicity, age, and where they attend university [ 6 , 20 , 21 , 22 , 23 ]. Barriers such as self-stigma, perceived need, and self-reliance influence when and how they seek help, while student’s also report a lack of awareness of appropriate services, concerns about confidentiality and discrimination, cost, or may perceive services to be ineffective or inappropriate [ 19 , 24 , 25 ]. These barriers may explain why some students only seek help in crisis and others tend to rely on informal sources of support [ 26 , 27 ]. International studies suggest very few students with need, receive support globally. One recent international cross-sectional study found 19.8% of first year university students, and 36% of those who may meet criteria for CMD report having ever used a mental health service, defined as medication or psychological counselling [ 6 ]. Compared to HICs, much less is known about students in Lower and Middle Income Countries (LMIC), although individual studies suggest very small numbers of students report accessing support when in distress [ 18 , 28 ].

While a limited number of studies have highlighted the scale and nature of the problem outside of the USA, there is a renewed effort to understand and address barriers to treatment that stop some students reaching help in the first place [ 4 , 16 , 27 ]. The World Health Organization’s (WHO) World Mental Health International College Student Initiative (WMH-ICS) aims to provide greater clarity on the unmet need of this group [ 16 ]. In the UK, there has been a policy focus on improving access to mental health interventions through greater integration between the National Health Service (NHS) and Universities, and an emphasis on mobilising university resources towards the mental health of students [ 29 , 30 ]. Previous reviews in the USA have looked at which students are most likely to seek help [ 20 , 31 ], however this is obviously confounded by the nature of services available to them. There are no systematic reviews conducted on the variety of services available to students internationally, how these integrate with each other and how use varies by types of service that deliver interventions to support mental health and wellbeing. Studies have examined individual services such as university counselling centres, external psychological services, or inpatient settings but have not compared the differential use of these by students with different clinical presentations. Given the developmental period in which many students attend university these settings are important in contributing to improving overall population mental health [ 3 , 32 ]. By understanding where variation occurs could indicate areas of differential access, highlighting where care pathways could be improved and inform policy initiatives.

This systematic review was conducted to address this gap, by answering two review questions: (1) what proportion of university students use mental health services when experiencing psychological distress? And (2) does utilisation differ across health service type?

This review was reported in accordance with PRISMA guidelines [ 33 ] (see Additional file 1 : Appendix S1). A protocol for this review was pre-registered on the 22/02/21 on PROSPERO ( https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42021238273 ).

Deviations from initial protocol

On the 26th of April 2021 we made an amendment to only include studies published in the year 2000 or after over concerns around changes to the student population that would create issues of comparability [ 4 ]. On the 27th of July 2021 we amended the focus of the review as the original aims were considered too broad for a coherent synthesis. The amendment removed one review question related to student characteristics associated with service use which could be explored in future analysis.

Eligibility criteria

Studies were included that:

Measured the use or utilisation of mental health services (as a primary or secondary outcome).

Studies that included adults (aged 18 +) studying at a university.

Studies were excluded:

That employed an empirical study design that aimed to test an intervention or approach to address or effect access or use of healthcare services.

Where it was not possible to extract sociodemographic and utilisation data for student participants.

Where participants under 18 were recruited.

Where participants weren’t all university students.

Studies needed to be published in English due to the languages spoken by the primary reviewer (TO).

Search strategy

The following electronic databases were searched on the 9th of March 2021, 3rd of November 2021 and the 23rd of August 2022: MEDLINE (Ovid); EMBASE (Ovid); PsycINFO (Ovid); ERIC (ESBCO); and CINAHL plus (ESBCO). The search strategy using a Context, Condition, Population (CoCoPop) framework with the concepts of “students”, “mental health/illness”, “access” and “mental health services” [ 34 ]. Key words and MeSH terms were developed in Medline between 2nd of December 2020 and 9th of March 2021, and adapted for each database (see Additional file 1 : Appendix S2). On the 16th and 17th of June 2021, the 14th of December 2021 and the 16th of November 2022 forward and backward citation searching was conducted. The publicly available reference list of studies published by the WHO’s WMH-ICS was searched on the 23rd of April 2021, the 14th of December 2021 and the 16th of November 2022. The authors of the originally included studies were contacted on the 18th of June 2021, where possible, to help identify any unpublished or ongoing research.

Data extraction

Records retrieved from electronic database searches were exported to Endnote X9, where duplicates were removed. Abstracts and full texts of potentially relevant articles were screened against the inclusion and exclusion criteria on Rayyan software. A random sample of approximately 10% of titles and abstracts identified in the initial searches were screened independently by a second reviewer (SL) using a purpose designed screening tool (see Additional file 1 : Appendix S3). Data from the included studies were extracted independently by two reviewers (TO and SL) using a pre-defined data extraction framework (see Additional file 1 : Appendix S4). Data were extracted into Excel. After data were extracted for two studies, the data extraction framework was checked for interpretation by both TO and SL. Study authors were contacted where additional data or clarification was required. The main items of interest were:

i Condition: use or utilisation

We defined use as the occurrence or number of uses of a mental health service over a defined time-period [ 35 ]. Indicators could include attendances, usage, inpatient days, admissions, contacts, episodes, or costs due to the receipt of treatment or attendance [ 35 ]. These indicators may be measured through self-report, clinical records, and/ or other routinely collected data. As observational or more naturalistic study designs were included in this review, outcomes are likely to be reported as prevalence or incidence and therefore as a proportion of the total study sample. Therefore, the effect measures were proportions with a 95% confidence interval as the main outcome [ 34 ].

ii Context: mental health service

An amended version of the WHO’s definition of a mental health service was used, this being ‘the means by which effective interventions are delivered for the dominant or subdominant intention to improve wellbeing or mental health’ [ 36 ]. This included outpatient services, day treatment, inpatient wards, community mental health teams, General Practice, mental health hospitals, and university counselling services [ 36 ]. To facilitate comparison of proportions by service type an adapted version of the Description and Evaluation of Services for Disabilities in Europe (DESDE) instrument was used (see Appendix S5) [ 37 ]. This is a hierarchical classification system, with six initial categories: (1) Information for care, (2) Accessibility to care, (3) Self-help and volunteer care, (4) Outpatient Care, (5) Day care, and (6) Residential care. A random 10% sample were double coded by two reviews (TO and SL). No service descriptions could be classified beyond the first level of the DESDE hierarchy. Therefore, to further specify, we used the National Institute for Health and Care Excellence (NICE) treatment stepped care categories, referred to as ‘treatment type’ [ 38 ], and the service location—being either on campus, off campus, or potentially either.

iii Other items

We also collected sociodemographic characteristics, study design, duration of study, data collection methods, data analysis methods, setting and date of study, raw data for the outcome, indicator(s) used, and time point(s) outcomes where reported, source of funding and conflicts of interest.

Quality assessment

We assessed risk of bias using the Joanna Briggs Institute (JBI) appraisal checklist for systematic review reporting prevalence data [ 34 ]. The checklist prompts the reviewer to answer nine questions with four possible response options: “yes”/ “no”/ “unclear”/ “not applicable”. Each study was assigned low, moderate, or high quality based on the number of yes answers it scored to indicate study quality. Studies with 1–3 ‘yes’ were low, 3–6 indicating moderate, and 7–9 as high quality. Quality appraisal was conducted independently on all studies meeting the inclusion criteria by two reviewers (TO and SL). Where there were disagreements, these were discussed until agreement was reached. No studies were excluded based on the study quality to enable sensitivity analyses to be conducted by removing studies rated as low quality.

Synthesis methods

I narrative synthesis.

Initially, a non-statistical narrative synthesis was conducted to describe the included studies relevant to the review questions [ 34 ]. Study participants and the measures of psychological symptoms were not universally well described. Therefore, the samples were qualitatively summarised and then categorised based on whether this was a general student sample, subgroup sample or a sample of students with more severe current psychological distress, referred to as ‘at risk’.

ii Meta-analysis

Most studies provided data for multiple service types, therefore three-level mixed effects models were used to account for clustering. Where the study provided a single estimate or an overall estimate of service use they were included in one of three conventional random effects meta-analytic models: (1) overall service use (any service), (2) overall outpatient service use, (3) overall residential service use reflecting the service types commonly observed in the data. Following this, to specifically test differences between these service types all estimates were then included into a three-level mixed effects model, where sub-group analysis and meta-regression were also conducted [ 39 ]. Further analyses were conducted for studies providing multiple estimates within the same study using two three-level mixed effects models to account for clustering: (1) outpatient service use; (2) service use where the service could be classed within multiple DESDE service categories.

For all pooled proportions, a priori subgroup analysis and meta-regression were conducted based on population group. Post-hoc analyses were conducted based on service location, treatment type, reporting timeframes, publication year, study design, and country, due to the substantial estimated heterogeneity. To conduct meta-regression for recall time-period a continuous variable was created based on the number of months participants were asked to recall service use (e.g., 12 months). If the reporting time-period did not use months (e.g., the student’s lifetime), it was estimated using the average age of the participants.

Heterogeneity was further explored by identifying outliers above or below the 95% confidence interval of the pooled proportion; by conducting influencer analysis; drafting a Baujat plot and conducting Graphic Display of Heterogeneity (GOSH) plots [ 39 ].

Sensitivity analyses were conducted for pooled estimates where low quality studies, estimates of lifetime service use and outliers and influential cases were excluded then all described analyses were repeated. Publication bias was not assessed due to the substantial between study heterogeneity [ 39 ].

Search results

A total of 7739 unique titles / abstracts were identified through database searches, and a further 52 through other search strategies (see Fig.  1 and Additional file 1 : Appendix S6). Inter-rater agreement for data screening was Cohen’s Kappa ( K ) = 0.85 indicating strong agreement [ 40 ].

PRISMA flow diagram

As a result of these search strategies, 44 studies were deemed eligible for inclusion. Within these studies there were 123 estimates of service use. Seven of these studies were smaller analyses of larger surveys conducted in the USA [ 23 , 41 , 42 , 43 , 44 , 45 , 46 ]. These seven studies were excluded from meta-analysis as their estimates would double count participants. 29 studies and 42 estimates were included in conventional two-level meta-analyses pooling estimates of overall service use, and then a three-level meta-analysis to test differences by service type. 25 studies and 60 estimates were included in further analyses using three-level meta-analysis. Inter-rater agreement for data extraction was K  = 0.82 indicating strong agreement [ 40 ].

Study characteristics

I study origin.

Studies were conducted in a range of mostly high-income countries. The majority were from the United States, where 34 of the 44 studies were based [ 9 , 23 , 41 , 42 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 56 , 57 , 58 , 59 , 60 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 ]. The remainder from Australia [ 73 , 74 ], Brazil [ 75 , 76 ], China [ 77 ], Canada [ 78 ], Ethiopia [ 79 ], Bangladesh [ 28 ], and Italy [ 80 ]. A total of nineteen studies were samples of students from separate individual universities [ 43 , 46 , 48 , 49 , 50 , 51 , 52 , 53 , 54 , 55 , 67 , 68 , 70 , 73 , 75 , 76 , 77 , 79 , 80 ]. Whereas the remaining twenty-four were samples across multiple universities [ 9 , 20 , 23 , 28 , 41 , 44 , 45 , 47 , 56 , 57 , 58 , 59 , 61 , 62 , 63 , 64 , 65 , 66 , 69 , 71 , 72 , 74 , 78 ].

ii Study design and methods

Most studies (n = 36) were either primary or secondary analyses of cross-sectional surveys [ 9 , 20 , 23 , 41 , 43 , 44 , 45 , 47 , 49 , 50 , 51 , 53 , 54 , 55 , 56 , 58 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 73 , 74 , 75 , 78 , 79 ] (see Table 1 ). Outcomes were assessed using standardised questionnaires and open questions. Of the remaining seven studies, one was a longitudinal study [ 46 ], one was a cohort study using a mix of a baseline survey and linked electronic medical records from the university counselling centre [ 77 ], two were secondary data analyses of electronic medical records from university counselling or health centres [ 52 , 59 , 60 ], and two were mixed method studies [ 48 , 80 ].

iii Study participants

Sample sizes varied substantially ranging from 15 to 730,785 participants. Most studies included general samples of student attending a university with fifteen studies studying specific subgroups of students [ 41 , 44 , 51 , 52 , 58 , 59 , 61 , 63 , 65 , 69 , 70 , 71 , 73 , 74 , 75 , 76 ]. Thirteen studies included samples of students ‘at risk’ [ 23 , 48 , 49 , 50 , 56 , 57 , 62 , 64 , 66 , 68 , 72 , 79 , 80 ]. Two studies sampled university faculty members, in addition to university students, although these participants were not asked about mental health service use [ 41 , 47 ]. One study included students at community college and 4-year institutions in the USA [ 23 ].

iv Mental health services

Overall, most estimates were associated with services classified into the outpatient service category of the DESDE instrument (see Table 2 ). Seventy-four estimates associated with thirty-seven studies were outpatient services [ 9 , 20 , 28 , 41 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 54 , 55 , 57 , 59 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 70 , 71 , 72 , 73 , 75 , 76 , 77 , 78 , 79 , 80 ]. Thirty-seven estimates associated with twenty-two studies could be classed as multiple service categories [ 9 , 20 , 23 , 41 , 47 , 50 , 53 , 56 , 57 , 61 , 62 , 63 , 64 , 65 , 66 , 68 , 69 , 70 , 71 , 74 , 78 ]. Residential service category was appropriate for seven estimates associated with five studies [ 9 , 57 , 61 , 66 , 70 ]. Inter-rater agreement for service coding was Κ  = 0.89, indicating strong agreement [ 40 ].

Across the service categories, 38 estimates related to services providing a range of treatments, 1 providing advice and support, 25 providing low intensity treatment, 35 related to high intensity treatment and 17 related to specialist treatment. Of these estimates thirteen related to services located off campus; 29 were on campus, whereas the remaining 79 estimates could have been located on or off a university campus.

v Defining and measuring use of health services

While all studies implicitly conceptualised mental health service use as an event or occurrence by a person in a time-period, the operational assessment was heterogeneous. In the cross-sectional and longitudinal studies, measurement varied by recall period and by item wording [ 9 , 20 , 23 , 28 , 41 , 43 , 44 , 45 , 47 , 49 , 50 , 51 , 53 , 54 , 55 , 56 , 58 , 61 , 62 , 63 , 64 , 65 , 66 , 67 , 68 , 69 , 70 , 71 , 72 , 73 , 74 , 75 , 78 , 79 ]. Only one study used a validated instrument assessing use over the previous two weeks [ 79 ], one asked student about their use over the previous two months [ 49 ], sixteen over the last 12 months [ 9 , 23 , 28 , 42 , 43 , 44 , 45 , 46 , 50 , 56 , 57 , 58 , 67 , 70 , 72 , 74 ], four while students were at university [ 41 , 47 , 68 , 71 ], and ten asked participants to report about previous use in their lifetime or ever [ 55 , 61 , 62 , 63 , 64 , 65 , 66 , 69 , 78 ]. One cross-sectional study asked student participants to both recall use of university counselling centre while at university, and the students use of other mental health service over their lifetime [ 66 ]. Nearly all cross-sectional studies gave participants a binary response option—either yes or no. Only one study used an ordered categorical response option where participants were asked to state whether they had used a particular service using a Likert scale ranging from 1–5 (never-often) [ 50 ]. Of the two mixed methods studies one reported current use [ 48 ], and the other reported on lifetime use [ 80 ]. Secondary analyses of electronic medical records examined number of unique visits per student over the study period [ 52 , 59 , 60 ].

Quality appraisal

Overall, the quality of the studies included in the review were moderate with around a quarter of the total samples rated as either high [ 43 , 44 , 45 , 46 , 56 , 67 , 72 , 79 ], or low quality [ 49 , 52 , 54 , 61 , 65 , 69 , 76 ]. The main area of weakness came from questions related to the validity and reliability of the assessment of mental health service use, with only six studies being rated as “yes” in both questions [ 45 , 46 , 56 , 67 , 74 , 79 ]. A further area of significant weakness was found in question eight which related to whether appropriate statistical analyses had been conducted with four studies rated as “yes” [ 49 , 53 , 59 , 63 ] (see Table 1 and Additional file 1 : Appendix S7). Inter-rater agreement for quality appraisal was Κ  = 0.88 indicating strong agreement [ 40 ].

What proportion of university students use mental health services when experiencing psychological distress?

I. overall use of any mental health service, narrative summary (n = 10; k = 11).

Ten studies reporting on students’ use of any mental health service use with estimates ranging between 13.7 and 68.6% of the study population reporting use [ 9 , 41 , 47 , 50 , 53 , 57 , 61 , 64 , 70 , 71 , 74 , 78 ]. Estimates ranged from 13.7 to 68.6% of the study population reporting using a service. It was difficult conclude the source of this variation. The highest estimate, at 68.6%, was the only for an on-campus service. Treatment offered by the service did not appear to be associated with variation across estimates. Broader operational service definitions tended to have higher estimates [ 53 , 74 ]. For example, in one study 49% of Chinese international students reported using “any form of help”, whereas all other estimates within the same study relating to specific services were low.

There was some evidence to suggest more severe current psychological distress was associated with higher previous mental health service use. For example, in studies with at risk samples reported estimates between 25.7 and 49% [ 50 , 57 , 74 ]. Whereas estimates in general populations of students had a lower range between 19.7 and 45% [ 9 , 47 , 53 , 78 ]. Variation also appeared to be related to the reporting period, where studies reporting on lifetime mental health service use tended to have higher estimates [ 61 , 78 ] (see Tables 1 and 2 ).

Meta-analysis (n = 9; k = 9)

The overall pooled proportion effect size using a random effects model was estimated to be 0.35 (95%CI: 0.22;0.50) (see Fig.  2 ). The between study heterogeneity was estimated at τ 2  = 0.69, and Ι 2  = 99.9%. The prediction interval ranged from 0.06 to 0.81. This indicated a wide range of future possible estimates. Overall, these results indicate substantial heterogeneity across the included estimates of mental health service use.

Forest plot for overall mental health service use by population group

Subgroups and meta-regressions for overall use

No variables were associated with an overall reduction in between study heterogeneity using meta-regressions. Subgroup analyses found differences by service location ( Q  = 40.41, df:2, p  < 0.001), and reporting period ( Q  = 5.92, df:2, p  = 0.05), However, meta-regressions found lower proportions were associated with off-campus service ( β  = − 1.35, 95%CI:− 2.52; − 0.18, p  =  0 .03), and higher proportions associated with longer reporting periods ( β  = 0.0043, 95%CI:− 0.001; 0.0075, p  = 0.02) (see Additional file 1 : Appendix S8).

ii Overall outpatient use

Narrative summary (n = 25; k = 27).

Twenty-five studies reported estimates of students overall outpatient service use with between 2.6 and 75% of the study populations reporting service use [ 9 , 28 , 41 , 43 , 44 , 45 , 46 , 47 , 48 , 49 , 50 , 51 , 52 , 54 , 57 , 59 , 61 , 62 , 63 , 66 , 67 , 69 , 70 , 71 , 72 , 73 , 75 , 76 , 77 , 80 ]. Use of on-campus services were lower ranging between 2.6 and 33.5% [ 9 , 41 , 47 , 50 , 51 , 52 , 58 , 59 , 60 , 66 , 69 , 73 , 77 ]. There was only one estimate of off-campus service use at 13.7% [ 49 ], whereas the remaining estimates were for services that could be either on or off campus between 7 and 75%. These differences could also be partly explained by differences in population group and treatment offered by the service. The lowest two estimates overall were in subgroups of students namely international students (2.6%) [ 52 ], and students in China (5.1%) [ 77 ], and among students Bangladeshi universities (7.1%) [ 28 ]. Whereas the highest estimates overall and in the category of either on campus or off campus services were in a study of medical students with more severe current psychological distress using services offering potentially any treatment (75%) [ 73 ]; previously homeless students or who had been in care where a broad service model had been developed for them (68%) [ 48 ], and veterinary students (62.5%) [ 61 ]. For this estimate participants reported against the use of “counselling”—which could have a broad interpretation in the USA. A further study also using a broad outpatient service definition was associated with a high estimate of 68% [ 49 ]. Overall, studies asking students to recall service use over their lifetime reported a higher range of estimates [ 61 , 62 , 63 , 69 , 80 ], compared to studies with shorter recall periods (see Tables 1 and 2 ).

Meta-analysis for overall outpatient use (n = 24; k = 26)

The overall pooled proportion effect size using a random effects model was estimated to be 0.21 (95%CI = 0.15;0.30) (see Fig.  3 ). The between study heterogeneity was estimated at τ 2  = 1.12 and Ι 2  = 99.9%. The prediction interval ranged from 0.03 to 0.72. This indicated a wide range of future possible estimates. Overall, these results indicate substantial heterogeneity across the included estimates of residential mental health service use.

Forest Plot for outpatient overall service use by population group

Sub-group analyses and meta-regressions for overall outpatient use

No meta-regression model resulted in a significant reduction in overall between-study heterogeneity. Subgroup analyses found overall differences by service location ( Q  = 9.03, df:1, p  = 0.002), population group ( Q  = 35.40, df:2, p  < 0.001), study design ( Q  = 94.68, df:3, p  < 0.001) (see Additional file 1 : Appendix S9). Meta-regressions were conducted finding lower proportions of service utilisation were associated with service providing low intensity treatment ( β  = − 0.91; 95%CI = − 1.78;− 0.04; p  = 0.04), and on campus services compared than those either on or off campus ( β  = − 1.10, 95%CI: − 1.85; − 0.36, p  = 0.005). Higher proportions of use were associated in ‘at risk’ to general populations of students ( β  = 1.62, 95%CI:0.88; 2.37, p  < 0.001), and mixed methods studies ( β  = 2.41, 95%CI:0.08; 4.73, p  = 0.04).

iii Overall residential service use

Narrative summary (n = 5; k = 7).

Four studies reported six estimates of residential service use [ 9 , 57 , 61 , 66 , 70 ], ranging from 1 to 5.4%. Population group appeared to be associated with this variation, with the study reporting on general populations of students having a lower estimate than other groups (see Tables 1 and 2 , and Additional file 1 : Appendix S10 for a detailed narrative summary).

Meta-analysis for overall residential service use (n = 5; k = 7)

The overall pooled proportion effect size using a random effects model was estimated to be 0.03 (95%CI:0.02;0.05) (see Fig.  4 ). The between study heterogeneity was estimated at τ 2  = 0.30, and Ι 2  = 99.4%. There was a prediction interval which ranged from a proportion of 0.007 to 0.12. This indicated a wide range of future possible estimates. Overall, these results indicate substantial heterogeneity across the included estimates of residential mental health service use.

Forest Plot for overall residential service use

Subgroup analyses and meta-regressions for overall residential service use

Meta-regressions only a found a reduction in between study heterogeneity association with population group (τ 2  = 0.19, Ι 2  = 86.6%). High estimates were associated with ‘at risk’ students ( β  = 1.29, 95%CI: 0.84; 1.73, p  = 0.001), and subgroup of students ( β  = 1.50, 95%CI: 0.80; 2.21, p  = 0.0041) when compared to general populations of students (see Additional file 1 : Appendix S10).

Does service use differ across health service type?

I differences in use by service type.

Subgroup analysis conducted using a three-level meta-analysis suggested differences between service types ( F  = 63.25, df:2,39, p  < 0.001). A meta-regression was conducted where compared to overall service use, both overall outpatient service and overall residential service use was associated with lower proportion of university students reporting using these services (outpatient: β  = − 0.77, 95%CI: − 1.26; − 0.29; p  = 0.01; residential: β  = − 3.05, 95%CI: − 3.63; − 2.47, p  < 0.001).

Sensitivity analyses found mixed results (see Table 3 ). For example, excluding estimates of lifetime service use had an attenuating effect on all pooled proportions, whereas removing low quality studies resulted in a lower pooled proportion only in overall service use. When outliers and influential estimates were removed the pooled proportion for overall service use was higher. A reduction in between study heterogeneity was only observed when outliers and influential cases were removed (see Table 3 ). Sensitivity analyses continued to suggest differences by service location and treatment type for overall outpatient service use, by service location for overall service use, except when excluding estimates of lifetime use (see Additional file 1 : Appendix S11, 12 and 13).

Further analyses using three-level meta-analysis

I estimates meeting multiple service categories, narrative summary (n = 12; k = 23).

Twelve studies reported on twenty-one estimates associated with services that could be classified as any DESDE classifications [ 9 , 47 , 53 , 55 , 56 , 62 , 63 , 64 , 65 , 70 , 74 , 78 ]. These estimates ranged from 5 to 68%. Lower estimates were reported in services offering specialist or high intensity treatment compared to a range of treatments, whereas higher estimates tended be in campus services. In general, studies asking students report service use over their lifetime were associated with higher estimates [ 55 , 62 , 63 , 64 , 65 , 78 ] (see Tables 1 and 2 ).

Meta-analysis (n = 12; k =  23)

The pooled proportion based on the three-level meta-analytic model was 0.20 (95%CI:0.13; 0.31, p < 0.001). Ι 2 level 3  = 82.9% of the total variation can be attributed to between-cluster, and  Ι 2 level 2  = 13.76% to within-cluster heterogeneity. We found that the three-level model provided a significantly better fit compared to a two-level model with level 3 heterogeneity constrained to zero (χ 2 1  = 8.10, p 0.004).

Subgroup analyses and meta-regressions

Subgroup analyses found differences by service location ( F  = 11.201, df:2,18, p  < 0.001). Meta regressions found on campus, and off campus location was associated with a high proportion when compared service potentially located in both locations (On campus: β  = 1.83, 95%CI:0.83, 2.83, p  = 0.001; off campus: β  = 0.91, 95%CI:0.003, 1.81, p  = 0.05) (see Additional file 1 : Appendix S14, and Appendix S16 for sensitivity analyses).

ii Specific outpatient services

Narrative summary (n = 13; k = 37).

Between 6.98% and 62.5% of students reporting outpatient service use out of the ten studies and twenty-seven estimates [ 49 , 55 , 61 , 64 , 65 , 66 , 67 , 68 , 70 , 71 , 76 , 79 ]. These estimates were between 6.98% and 62.5% of the study populations reporting outpatient service use. It was difficult to determine what this variation was associated with. The definitions used to measure service use may explain some variation. For example, the highest estimate of 62.5% related to individual counselling, and lowest estimate of 6.98% related to group counselling within the same study, and both classed as low intensity treatments [ 61 ]. The country a service was located appeared to potentially be associated with some variation. Estimates in a study of students at risk in Ethiopia were both low compared to most other estimates in the USA [ 79 ]. In general, higher estimates tended to be in studies asking students to report whether they had ever used a mental health service [ 49 , 55 , 61 , 64 , 65 , 68 , 78 ].

Meta-analysis (n = 13; k = 37)

The pooled proportion based on the three-level meta-analytic model was 0.19 (95%CI:0.13; 0.28, p  < 0.001). Ι 2 level 3  = 31.3% of the total variation can be attributed to between-cluster, and  Ι 2 level 2  = 64.3% to within-cluster heterogeneity. We did not find that the three-level model provided a significantly better fit compared to a two-level model with level 3 heterogeneity constrained to zero (χ 2 1  = 1.99, p  = 0.16).

Subgroup analyses found differences by treatment type ( F  = 34.83, df:3,33, p  < 0.001) and service location ( F  = 35.58, df:2,34, p  < 0.001). Meta regressions found low intensity ( β  = − 0.94, 95%CI: − 1.17, − 0.71, p  <  0.0 01), specialist treatment ( β  = − 2.06, 95%CI: − 2.81, − 1.32, p  <  0.0 01) and on campus locations were associated with lower proportions ( β  = − 0.93, 95%CI: − 1.15, − 0.71, p  < 0.001) (see Additional file 1 : Appendix S15, and Appendix S17 for sensitivity analyses).

Main findings

This is the first systematic review and meta-analysis to synthesize evidence relating to the proportion of university students using mental health services, and how this varies by service type. In summary, we found there are wide variety of services available taking varying proportions of students, although overwhelmingly these were from HICs, in particular the USA. Across studies when estimates were grouped and pooled in service categories, we found around a 1/3 of students use services overall while attending university, with around 1/5 of students using outpatient services, and between 1 and 3% have used services that could be classed as residential. Our findings suggest where there is greater availability of support there is greater use, as indicated by higher use being associated with services offering a range of treatments. There was limited evidence to suggest services on campus were used more than those off campus, and students with more severe current psychological distress were associated with greater past service use. However, there are significant limitations with the current literature, including few international studies, particularly from LMICs, little clarity on how services link together, no studies of patient flow and limited consistent description of services.

Findings in the context of existing evidence

The finding of the proportion of students using mental health services is broadly consistent with average proportions of students reporting problems in previous literature from the USA and North America. In 2012 around 18% of students reported receiving any form of mental health treatment, and 36% among students with a likely mental health problem [ 20 ]. Annual cross-sectional surveys confirm that service use is aligned with prevalence in the USA and Canada with increases in service utilisation between 2007 and 2017 to around one third of university students using services [ 8 , 9 ]. Comparisons with estimates in non-student populations are difficult to interpret because of heterogeneous measures used to estimate need, limited international longitudinal analyses, and few studies assessing the effect of university on mental health trajectories [ 4 ]. A systematic review of service use among non-student young adults found only 16% reported using any mental health service, lower than our findings [ 81 ]. This is unlikely to be due to differences in need as individual studies suggest mental disorder has increased in both groups, at a similar rate [ 10 , 11 ]. US studies featured predominantly in both this previous review and ours, therefore differences in reported service use may reflect differences in the availability of services and insurance coverage between groups in the USA. Studies in non-students included relatively young populations with an average age of 21 [ 81 ]. In the USA context, the transition to university could prompt the earlier emergence of mental health difficulties as students may face significant new pressures, a new social context and new financial challenges prompting earlier help seeking [ 4 , 9 , 20 , 25 , 27 , 82 ].

Our review predominantly reports on studies of US university students in four-year institutions, and therefore our findings likely confounded by what is available there. Higher proportions of students using campus services maybe due to student’s awareness of, and ability to reach and pay for these services in comparison to other services [ 83 ]. Four-year US institutions receive comparably higher levels of funding than US community colleges, influencing their ability to provide students with comprehensive mental health services [ 23 , 47 , 84 ]. Studies using both national and regional US samples found four-year university students report higher use of services on campus compared to community college students, despite higher prevalence of mental health problems in community colleges [ 23 , 47 ]. Cost was cited as the most common barrier to seeking help among community college students [ 23 ]. International studies included in this review reported different patterns of service use, which may reflect different patterns of service provision, demand among students, and barriers to help seeking [ 73 , 74 , 75 , 78 , 79 , 80 ]. For example, countries such as Australia where there may be fewer barriers to support outside of university, students sought help from a broad range of providers, most frequent being General Practitioners [ 73 ]. The limited number of studies outside the USA may reflect the relatively recent increases in the number and diversity of students attending university in other HIC countries, such as the UK [ 4 ]. Only recent research has highlighted the very limited research focus on LMIC [ 85 ], perhaps the reflecting the potentially smaller proportion of their national populations attending university compared to most HICs [ 1 ]. However, recent efforts through the WHO WMH-ICS indicates some change in this field [ 6 , 16 ]. This in the context of the growing emphasis on the importance of global mental health and the role higher education might play in contributing to improvements in population health [ 1 , 3 ].

The level of heterogeneity observed was striking when compared to the published literature potentially illustrating the wide range of services, likely with a range of entry requirements, and populations of students. This could also reflect inequalities in population coverage and use of mental health services relative to need across the student populations, as noted in other literature [ 18 , 21 , 22 ]. A review in non-student populations found being female, Caucasian, homosexual, or bisexual meant you were more likely to use services, which is similar to findings in students [ 81 ]. However, in our review, some studies of international students had comparably lower use of services, one study reporting only 2.6% used a service [ 52 ]. Other studies examining use in other populations in our review reported much higher proportions, as high as 75% [ 73 ]. It may be that variation among students is even greater than non-students due to the wide variety of needs among students. Despite students in the USA and other HICs potentially having more available services, such as those on campus, these may be particularly underutilised by some groups who experience more significant barriers to help-seeking both inside and outside university [ 18 , 21 , 22 ]. If some groups of students are consistently underrepresented in services, it is unlikely activities and interventions these services provide will be appropriate for their needs, and will continue to be underutilised by these students [ 86 ].

Strengths and limitations

This is the first systematic review to summarise and pool evidence quantitatively about the management of student mental health. This allowed us to explore and then quantify variation in the way mental health services are used by university students. However, there are limitations to the current review. Firstly, generalising the findings of this review outside of the USA should be cautioned given the limited number of international studies. Secondly, there were specific challenges to classifying services studies described or listed. For example, it was not always clear whether the services were interpreted in the same way by all participants or services with similar names were comparable to each other between studies. While we double coded a random sample of these services, this could have introduced classification bias when grouping the services in this review. We found some outlying estimates that may have been explained by the broad definitions used. For example, ‘counselling’ could provide help for a range of needs or be interpreted differently by students answering a survey. While other reviews have commented that there is variation by treatment received, service location, and by specific populations of students [ 20 , 31 ]. There was not always detailed and consistent data across our included studies to thoroughly evaluate these relationships quantitatively. However, we used a range of synthesis methods to understand the literature.

The methods to examine use of mental health services in the included studies were heterogeneous. While most included binary response options, the reporting periods varied. This meant there were challenges determining whether students used a service at university or before they were students and whether students continued to use services from before university or were new presentations. This may have led to an overestimation of the proportion of students using mental health services. However, we did conduct sensitivity analyses where we excluded these estimates and used meta-regressions to control for reporting period in all analyses. Most of the studies were in the USA. We would therefore caution generalising the findings of this review beyond the USA given the specificities of the healthcare system and infrastructure available to students there, in contrast even to other Western countries.

Implications for practice, policy, and research

The findings from this review emphasise the importance of a range of service provision being available to students who are experiencing psychological distress, and supports current policy efforts to develop well integrated services to help span levels of need. However, reviews in countries with a significant policy emphasis on integration, such as the UK, highlight the challenges defining this process, and the traditionally top-down approach has led to mixed success [ 87 ]. The authors argue this may relate to the highly contextual nature of the problems integration aims to address, therefore it should focus on what needs to be done rather than simply the goal of integration [ 87 ]. The findings of our review, particularly the variety of services, groups of students and numbers using mental health services, support this point. This emphasises the need for detailed local needs assessments, the co-production of the process of integration with relevant stakeholders, and adaptations to meet the needs of the local student population [ 32 , 87 ].

Given the important developmental period students often attend university and the potential important role university’s could play in improving population mental health, the findings of the review suggest a series of important avenues for future research. (1) There is a urgent need to conduct robust international studies to understand student mental health need; (2) international research describing service models available to, acceptable to, and used by, students and similar aged young people; (3) given the few students using formal mental health services across all studies identified in this review, international research should continue to understand alternative models and interventions which might be acceptable and accessible students, such as task shifting, the use of technology, and capacity building within social networks [ 3 , 32 ]; (4) there are no studies of patient flow and how services are linked together which should be a priority of research particularly given the policy emphasis on integration; (5) there is a limited number of studies examining the adequacy of treatment students receive which could help understand how well services are meeting the needs of students who reach services [ 42 ]. (6) To understand how best to adapt current care pathways the experiences of students, healthcare professionals and other stakeholders need to be explored. In some HICs qualitative studies have spoken to students, and staff in counselling services [ 19 , 24 , 25 , 82 ], however given the variation of services we found in this review our findings emphasize the need to speak to healthcare professionals, students and other young in a range of settings; (7) The observed differences between the findings of this review and a review in non-student populations [ 81 ], it is crucial to understand whether university attendance adds additional risk to mental health trajectories. Our findings suggest significant inequalities in access to mental health services among students and settings, the literature should be systematically reviewed to examine this further.

Globally, future research should pay close attention to health and social inequalities between those with and without a university degree. In many countries, particularly those with a small proportions of people ultimately attaining a university degree, there is the potential to exacerbate inequalities by improving the health of a potentially privileged group of people [ 1 , 88 ]. Any initiatives aiming to address student mental health should be considered in the relation to wider population as part of a broader strategy to improve population mental health [ 3 ].

This review is the first effort to systematically describe mental health services available to students and quantify students’ use of them. Most studies were in HICs, in particularly the USA, where we found around a third of students had used a mental health service, similar to the proportion of students with symptoms indicative of mental disorder. However, we found significant variation in the utilisation of mental health services across populations of students, settings, and countries. There were some services, such as those on-campus, used more than others potentially reflecting supply and demand patterns in the included study settings. The empirical literature to date is very limited in terms of the relatively small number of international studies, and few studies examining how services link together, and how students move between them which limits our understanding of the problems students face. Our findings support the current renewed effort to study student mental health internationally and emphasises the importance of well-integrated services to support students’ needs.

Availability of data and materials

The datasets used and/or analysed during the current study are available from the corresponding author on reasonable request. Other materials are available in Additional file 1 : Appendices 1–17.

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Acknowledgements

Professor Steve Pilling, Dr Laura Gibbon and Dr Emma Broglia for their advice on the design and conduct of this review.

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Additional file 1..

Appendix S1. PRISMA checklist. Appendix S2. Key words and MeSH terms. Appendix S3. Screening tool and eligibility assessment tool. Appendix S4. Data Extraction Form (2). Appendix S5. Relevant Sections from the eDESDE-LTC coding framework used for coding services. Appendix S6. search results. Appendix S7. Quality Appaisal (2). Appendix S8. Overall service use. Appendix S9. Overall outpatient service use. Appendix S10. Overall residential service use. Appendix S11. Sensitivity analyses. Appendix S12. Sensitivity analyses – overall service use. Appendix S13. Sensitivity analyses – overall outpatient service use. Appendix S14. Specific service use (multiple DESDE categories) analyses. Appendix S15. Specific outpatient service use analyses. Appendix S16. Sensitivity analyses - specific service use (multiple DESDE categories). Appendix S17. Sensitivity analyses - specific outpatient service use.

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• 13 November 2019

The mental health of PhD researchers demands urgent attention

You have full access to this article via your institution.

Performance management — captured here in photographs from Frank Gilbreth — has long contributed to ill health in researchers. Credit: Kheel Centre

Two years ago, a student responding to Nature ’s biennial PhD survey called on universities to provide a quiet room for “crying time” when the pressures caused by graduate study become overwhelming. At that time , 29% of 5,700 respondents listed their mental health as an area of concern — and just under half of those had sought help for anxiety or depression caused by their PhD study.

Things seem to be getting worse.

Respondents to our latest survey of 6,300 graduate students from around the world, published this week, revealed that 71% are generally satisfied with their experience of research, but that some 36% had sought help for anxiety or depression related to their PhD.

These findings echo those of a survey of 50,000 graduate students in the United Kingdom also published this week. Respondents to this survey, carried out by Advance HE, a higher-education management training organization based in York, UK, were similarly positive about their research experiences, but 86% report marked levels of anxiety — a much higher percentage than in the general population. Similar data helped to prompt the first international conference dedicated to the mental health and well-being of early-career researchers in May. Tellingly, the event sold out .

How can graduate students be both broadly satisfied, but also — and increasingly — unwell? One clue can be found elsewhere in our survey. One-fifth of respondents reported being bullied; and one-fifth also reported experiencing harassment or discrimination.

Could universities be taking more effective action? Undoubtedly. Are they? Not enough. Of the respondents who reported concerns, one-quarter said that their institution had provided support, but one-third said that they had had to seek help elsewhere.

There’s another, and probably overarching, reason for otherwise satisfied students to be stressed to the point of ill health. Increasingly, in many countries, career success is gauge by a spectrum of measurements that include publications, citations, funding, contributions to conferences and, now, whether a person’s research has a positive impact on people, the economy or the environment. Early-career jobs tend to be precarious. To progress, a researcher needs to be hitting the right notes in regard to the measures listed above in addition to learning the nuts and bolts of their research topics — concerns articulated in a series of columns and blog posts from the research community published last month.

Most students embark on a PhD as the foundation of an academic career. They choose such careers partly because of the freedom and autonomy to discover and invent. But problems can arise when autonomy in such matters is reduced or removed — which is what happens when targets for funding, impact and publications become part of universities’ formal monitoring and evaluation systems. Moreover, when a student’s supervisor is also the judge of their success or failure, it’s no surprise that many students feel unable to open up to them about vulnerabilities or mental-health concerns.

The solution to this emerging crisis does not lie solely in institutions doing more to provide on-campus mental-health support and more training for supervisors — essential though such actions are. It also lies in recognizing that mental ill-health is, at least in part, a consequence of an excessive focus on measuring performance — something that funders, academic institutions, journals and publishers must all take responsibility for.

Much has been written about how to overhaul the system and find a better way to define success in research, including promoting the many non-academic careers that are open to researchers. But on the ground, the truth is that the system is making young people ill and they need our help. The research community needs to be protecting and empowering the next generation of researchers. Without systemic change to research cultures, we will otherwise drive them away.

Nature 575 , 257-258 (2019)

doi: https://doi.org/10.1038/d41586-019-03489-1

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Expert Commentary

Improving college student mental health: Research on promising campus interventions

Hiring more counselors isn’t enough to improve college student mental health, scholars warn. We look at research on programs and policies schools have tried, with varying results.

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This work is licensed under a Creative Commons Attribution-NoDerivatives 4.0 International License .

by Denise-Marie Ordway, The Journalist's Resource September 13, 2023

This <a target="_blank" href="https://journalistsresource.org/education/college-student-mental-health-research-interventions/">article</a> first appeared on <a target="_blank" href="https://journalistsresource.org">The Journalist's Resource</a> and is republished here under a Creative Commons license.<img src="https://journalistsresource.org/wp-content/uploads/2020/11/cropped-jr-favicon-150x150.png" style="width:1em;height:1em;margin-left:10px;">

If you’re a journalist covering higher education in the U.S., you’ll likely be reporting this fall on what many healthcare professionals and researchers are calling a college student mental health crisis.

An estimated 49% of college students have symptoms of depression or anxiety disorder and 14% seriously considered committing suicide during the past year, according to a national survey of college students conducted during the 2022-23 school year. Nearly one-third of the 76,406 students who participated said they had intentionally injured themselves in recent months.

In December, U.S. Surgeon General Vivek Murthy issued a rare public health advisory calling attention to the rising number of youth attempting suicide , noting the COVID-19 pandemic has “exacerbated the unprecedented stresses young people already faced.”

Meanwhile, colleges and universities of all sizes are struggling to meet the need for mental health care among undergraduate and graduate students. Many schools have hired more counselors and expanded services but continue to fall short.

Hundreds of University of Houston students held a protest earlier this year , demanding the administration increase the number of counselors and make other changes after two students died by suicide during the spring semester, the online publication Chron reported.

In an essay in the student-run newspaper , The Cougar, last week, student journalist Malachi Key blasts the university for having one mental health counselor for every 2,122 students, a ratio higher than recommended by the International Accreditation of Counseling Services , which accredits higher education counseling services.

But adding staff to a campus counseling center won’t be enough to improve college student mental health and well-being, scholars and health care practitioners warn.

“Counseling centers cannot and should not be expected to solve these problems alone, given that the factors and forces affecting student well-being go well beyond the purview and resources that counseling centers can bring to bear,” a committee of the National Academies of Sciences, Engineering, and Medicine writes in a 2021 report examining the issue.

Advice from prominent scholars

The report is the culmination of an 18-month investigation the National Academies launched in 2019, at the request of the federal government, to better understand how campus culture affects college student mental health and well-being. Committee members examined data, studied research articles and met with higher education leaders, mental health practitioners, researchers and students.

The committee’s key recommendation: that schools take a more comprehensive approach to student mental health, implementing a wide range of policies and programs aimed at preventing mental health problems and improving the well-being of all students — in addition to providing services and treatment for students in distress and those with diagnosed mental illnesses.

Everyone on campus, including faculty and staff across departments, needs to pitch in to establish a new campus culture, the committee asserts.

“An ‘all hands’ approach, one that emphasizes shared responsibility and a holistic understanding of what it means in practice to support students, is needed if institutions of higher education are to intervene from anything more than a reactive standpoint,” committee members write. “Creating this systemic change requires that institutions examine the entire culture and environment of the institution and accept more responsibility for creating learning environments where a changing student population can thrive.”

In a more recent analysis , three leading scholars in the field also stress the need for a broader plan of action.

Sara Abelson , a research assistant professor at Temple University’s medical school; Sarah Lipson , an associate professor at the Boston University School of Public Health; and Daniel Eisenberg ,  a professor of health policy and management at the University of California, Los Angeles’ School of Public Health, have been studying college student mental health for years.

Lipson and Eisenberg also are principal investigators for the Healthy Minds Network , which administers the Healthy Minds Study , a national survey of U.S college students conducted annually to gather information about their mental health, whether and how they receive mental health care and related issues.

Abelson, Lipson and Eisenberg review the research to date on mental health interventions for college students in the 2022 edition of Higher Education: Handbook of Theory and Research . They note that while the evidence indicates a multi-pronged approach is best, it’s unclear which specific strategies are most effective.

Much more research needed

Abelson, Lipson and Eisenberg stress the need for more research. Many interventions in place at colleges and universities today — for instance, schoolwide initiatives aimed at reducing mental health stigma and encouraging students to seek help when in duress – should be evaluated to gauge their effectiveness, they write in their chapter, “ Mental Health in College Populations: A Multidisciplinary Review of What Works, Evidence Gaps, and Paths Forward .”

They add that researchers and higher education leaders also need to look at how campus operations, including hiring practices and budgetary decisions, affect college student mental health. It would be helpful to know, for example, how students are impacted by limits on the number of campus counseling sessions they can have during a given period, Abelson, Lipson and Eisenberg suggest.

Likewise, it would be useful to know whether students are more likely to seek counseling when they must pay for their sessions or when their school charges every member of the student body a mandatory health fee that provides free counseling for all students.

“These financially-based considerations likely influence help-seeking and treatment receipt, but they have not been evaluated within higher education,” they write.

Interventions that show promise

The report from the National Academies of Sciences, Engineering, and Medicine and the chapter by Abelson, Lipson and Eisenberg both spotlight programs and policies shown to prevent mental health problems or improve the mental health and well-being of young people. However, many intervention studies focus on high school students, specific groups of college students or specific institutions. Because of this, it can be tough to predict how well they would work across the higher education landscape.

Scientific evaluations of these types of interventions indicate they are effective:

• Building students’ behavior management skills and having them practice new skills under expert supervision . An example: A class that teaches students how to use mindfulness to improve their mental and physical health that includes instructor-led meditation exercises.
• Training some students to offer support to others , including sharing information and organizing peer counseling groups. “Peers may be ‘the single most potent source of influence’ on student affective and cognitive growth and development during college,” Abelson, Lipson and Eisenberg write.
• Reducing students’ access to things they can use to harm themselves , including guns and lethal doses of over-the-counter medication.
• Creating feelings of belonging through activities that connect students with similar interests or backgrounds.
• Making campuses more inclusive for racial and ethnic minorities, LGBTQ+ students and students who are the first in their families to go to college. One way to do that is by hiring mental health professionals trained to recognize, support and treat students from different backgrounds. “Research has shown that the presentation of [mental health] symptoms can differ based on racial and ethnic backgrounds, as can engaging in help-seeking behaviors that differ from those of cisgender, heteronormative white men,” explain members of National Academies of Sciences, Engineering, and Medicine committee.

Helping journalists sift through the evidence

We encourage journalists to read the full committee report and aforementioned chapter in Higher Education: Handbook of Theory and Research . We realize, though, that many journalists won’t have time to pour over the combined 304 pages of text to better understand this issue and the wide array of interventions colleges and universities have tried, with varying success.

To help, we’ve gathered and summarized meta-analyses that investigate some of the more common interventions. Researchers conduct meta-analyses — a top-tier form of scientific evidence — to systematically analyze all the numerical data that appear in academic studies on a given topic. The findings of a meta-analysis are statistically stronger than those reached in a single study, partly because pooling data from multiple, similar studies creates a larger sample to examine.

Keep reading to learn more. And please check back here occasionally because we’ll add to this list as new research on college student mental health is published.

Peer-led programs

Stigma and Peer-Led Interventions: A Systematic Review and Meta-Analysis Jing Sun; et al. Frontiers in Psychiatry, July 2022.

When people diagnosed with a mental illness received social or emotional support from peers with similar mental health conditions, they experienced less stress about the public stigma of mental illness, this analysis suggests.

The intervention worked for people from various age groups, including college students and middle-aged adults, researchers learned after analyzing seven studies on peer-led mental health programs written or published between 1975 and 2021.

Researchers found that participants also became less likely to identify with negative stereotypes associated with mental illness.

All seven studies they examined are randomized controlled trials conducted in the U.S., Germany or Switzerland. Together, the findings represent the experiences of a total of 763 people, 193 of whom were students at universities in the U.S.

Researchers focused on interventions designed for small groups of people, with the goal of reducing self-stigma and stress associated with the public stigma of mental illness. One or two trained peer counselors led each group for activities spanning three to 10 weeks.

Five of the seven studies tested the Honest, Open, Proud program, which features role-playing exercises, self-reflection and group discussion. It encourages participants to consider disclosing their mental health issues, instead of keeping them a secret, in hopes that will help them feel more confident and empowered. The two other programs studied are PhotoVoice , based in the United Kingdom, and

“By sharing their own experiences or recovery stories, peer moderators may bring a closer relationship, reduce stereotypes, and form a positive sense of identity and group identity, thereby reducing self-stigma,” the authors of the analysis write.

Expert-led instruction

The Effects of Meditation, Yoga, and Mindfulness on Depression, Anxiety, and Stress in Tertiary Education Students: A Meta-Analysis Josefien Breedvelt; et al. Frontiers in Psychiatry, April 2019.

Meditation-based programs help reduce symptoms of depression, anxiety and stress among college students, researchers find after analyzing the results of 24 research studies conducted in various parts of North America, Asia and Europe.

Reductions were “moderate,” researchers write. They warn, however, that the results of their meta-analysis should be interpreted with caution considering studies varied in quality.

A total of 1,373 college students participated in the 24 studies. Students practiced meditation, yoga or mindfulness an average of 153 minutes a week for about seven weeks. Most programs were provided in a group setting.

Although the researchers do not specify which types of mindfulness, yoga or meditation training students received, they note that the most commonly offered mindfulness program is Mindfulness-Based Stress Reduction and that a frequently practiced form of yoga is Hatha Yoga .

Meta-Analytic Evaluation of Stress Reduction Interventions for Undergraduate and Graduate Students Miryam Yusufov; et al. International Journal of Stress Management, May 2019.

After examining six types of stress-reduction programs common on college campuses, researchers determined all were effective at reducing stress or anxiety among students — and some helped with both stress and anxiety.

Programs focusing on cognitive-behavioral therapy , coping skills and building social support networks were more effective in reducing stress. Meanwhile, relaxation training, mindfulness-based stress reduction and psychoeducation were more effective in reducing anxiety.

The authors find that all six program types were equally effective for undergraduate and graduate students.

The findings are based on an analysis of 43 studies dated from 1980 to 2015, 30 of which were conducted in the U.S. The rest were conducted in Australia, China, India, Iran, Japan, Jordan, Kora, Malaysia or Thailand. A total of 4,400 students participated.

Building an inclusive environment

Cultural Adaptations and Therapist Multicultural Competence: Two Meta-Analytic Reviews Alberto Soto; et al. Journal of Clinical Psychology, August 2018.

If racial and ethnic minorities believe their therapist understands their background and culture, their treatment tends to be more successful, this analysis suggests.

“The more a treatment is tailored to match the precise characteristics of a client, the more likely that client will engage in treatment, remain in treatment, and experience improvement as a result of treatment,” the authors write.

Researchers analyzed the results of 15 journal articles and doctoral dissertations that examine therapists’ cultural competence . Nearly three-fourths of those studies were written or published in 2010 or later. Together, the findings represent the experiences of 2,640 therapy clients, many of whom were college students. Just over 40% of participants were African American and 32% were Hispanic or Latino.

The researchers note that they find no link between therapists’ ratings of their own level of cultural competence and client outcomes.

Internet-based interventions

Internet Interventions for Mental Health in University Students: A Systematic Review and Meta-Analysis Mathias Harrer; et al. International Journal of Methods in Psychiatric Research, June 2019.

Internet-based mental health programs can help reduce stress and symptoms of anxiety, depression and eating disorders among college students, according to an analysis of 48 research studies published or written before April 30, 2018 on the topic.

All 48 studies were randomized, controlled trials of mental health interventions that used the internet to engage with students across various platforms and devices, including mobile phones and apps. In total, 10,583 students participated in the trials.

“We found small effects on depression, anxiety, and stress symptoms, as well as moderate‐sized effects on eating disorder symptoms and students’ social and academic functioning,” write the authors, who conducted the meta-analysis as part of the World Mental Health International College Student Initiative .

The analysis indicates programs that focus on cognitive behavioral therapy “were superior to other types of interventions.” Also, programs “of moderate length” — one to two months – were more effective.

The researchers note that studies of programs targeting depression showed better results when students were not compensated for their participation, compared to studies in which no compensation was provided. The researchers do not offer possible explanations for the difference in results or details about the types of compensation offered to students.

About The Author

Denise-Marie Ordway

Mental Health of College Students Is Getting Worse

The COVID-19 pandemic took a toll on many college students, but researchers did not find a huge spike in reported mental health problems during the semesters of the pandemic. Rather they saw a continuation of a troubling trend. Photo by iStock/lightspeedshutter

The rate of mental health problems, including anxiety and depression, has steadily increased over the past eight years, with rates even higher among racial and ethnic minority students

Jessica colarossi.

To say that college years are a time of great change is an understatement; whether you stay at or close to home, or move away to a four-year university, the post–high school years are often a time of new experiences, unfamiliar responsibilities, growing pains, and learning curves. They can also be a time when some students have to navigate their own physical and mental health for the first time without parental support.

“College is a key developmental time; the age of onset for lifetime mental health problems also directly coincides with traditional college years—75 percent of lifetime mental health problems will onset by age 24,” says Sarah K. Lipson , a Boston University School of Public Health assistant professor of health law, policy, and management. For more than 10 years, she’s studied college student mental health with the Healthy Minds Network , a national project she coleads with researchers at the University of California, Los Angeles, the University of Michigan, and Wayne State University. 

In a new study , Lipson and her colleagues reveal just how common depression, anxiety, and other mental health issues are, and how these issues take a toll on students of color unequally. The paper looks at survey data collected by the Healthy Minds Network between 2013 and 2021 from 350,000 students at over 300 campuses. It’s the first long-term, multicampus study of its kind to parse out differences in treatment and prevalence of mental health issues across race and ethnicity. The study was coauthored by Lipson and other members of the Healthy Minds Network team. 

“As a budding clinician of color, I think the tracking of these trends helps support efforts related to stigma reduction and [mental health] education that can be targeted toward certain communities,” says Jasmine Morigney , a clinical psychology doctoral student at Eastern Michigan University and a coauthor on the study.

The researchers used screening tools to measure mental health symptoms, levels of flourishing, and whether a student received treatment during their time at college; participants self-identified their race and ethnicity.

They found that the mental health of college students across the United States has been on a consistent decline for all eight years of data analyzed, with an overall 135 percent increase in depression and 110 percent increase in anxiety from 2013 to 2021; the number of students who met the criteria for one or more mental health problems in 2021 had doubled from 2013. 

Need for Mental Health Support Outpacing Resources 

American Indian/Alaskan Native college students were found to have the largest increases in depression, anxiety, suicidal ideation, and other mental health problems, as well as the largest decreases in flourishing. Back in 2016, about a third of American Indian/Alaskan Native students screened positive for depression, a similar level to other racial and ethnic groups in the study. But by the 2019 and 2020 semesters, half of those respondents were screening positive for depression.

“There has not been nearly enough research on this population,” Lipson says. “My hope is that these data document the urgency around understanding some of the unique factors shaping these students’ mental health. American Indian/Alaskan Native students need to be brought into the conversation for universities to invest in resources that align with their preferences.”  

For white students, the prevalence of non-suicidal self-injury and symptoms of eating disorders increased most significantly compared to other groups. In all other categories—depression, anxiety, suicidal ideation, and one or more mental health problems—increases were seen the most among non-white students. During the semesters of the COVID-19 pandemic, American Indian/Alaskan Native students and Asian/Pacific Islander/Desi American (APIDA) students reported the most significant increases in mental health concerns, according to the data. 

Although more students overall are seeking help and access to mental health services on college campuses than they were in 2013—which is good news, says Lipson—the prevalence of mental health issues seems to be outpacing the number of students finding and receiving support. And some groups of students are actually less likely to get help than a decade ago. For example, Arab American students experienced a 22 percent jump in mental health issues, but had an 18 percent decrease in treatment over the eight years of the study, highlighting a critical gap between onset of symptoms and accessing help. During the semesters of the pandemic—when many schools went remote—fewer students of color were accessing necessary services. 

“I find the change in treatment rates among students of color in the context of the COVID-19 pandemic to be quite surprising,” Morigney says. Treatment declined the most in 2020 among APIDA and Black students. “Given the impact of the pandemic on this community and concentrated traumatic racism, it makes this finding quite alarming,” she says. 

Not Just a Pandemic Problem

Though researchers tracked significant increases in anxiety and depression during the height of the COVID-19 pandemic, Lipson says the numbers show a continuation of a troubling trend rather than a singular spike.  

“The crisis related to mental health exists beyond the college and university setting,” Lipson says. But the potential to intervene and reach students at a uniquely important time of life is huge. “It might not be perfect, but many four-year colleges offer some of the best resources people will ever have,” Lipson says, since these institutions can use their resources to remove many barriers to care, such as a lack of available providers, long wait times, and financial restraints. 

University policies to address and eliminate racial discrimination on campus and in healthcare settings can also reduce the mental health risk factors that many students of color experience.  

“I would love to see universities work to enhance and promote diversity in their behavioral health staff,” says Morigney. Students of color may not know if their campus counseling centers have staff with similar cultural backgrounds and could be reluctant to seek out services, she says. “The majority of mental health professionals are white, and universities are critical for not only providing students with culturally and ethnically diverse care, but also providing opportunities for clinicians of color to serve these student bodies.” Providing training opportunities to encourage students of color to enter the field of mental health is also a huge opportunity. 

“One of the most important aspects of this study is documenting these inequalities and communicating them to folks who can use this information to enact change,” Lipson says. For colleges across the country worried about retention rates— many colleges are seeing more students quit before completing their studies —she says the conversations about retaining students and mental health need to be brought together. It’s often the “same students who have the lowest rate of retention in higher education [who] are the same students who are least likely to access mental health services when they are struggling, and mental health is a predictor of retention,” she says. 

“In the big picture, we need to bring mental health into the classroom so that it doesn’t require a student needing to make time or getting motivated to seek help,” Lipson says. “There is a lot we can do to bring mental health into the default of students’ lives.”

BU students seeking support can reach out to  Student Health Services ; faculty, staff, and employee family members can contact BU’s  Faculty & Staff Assistance Office  for help with work and life challenges.

This work was supported by the National Institutes of Health.

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There are 16 comments on Mental Health of College Students Is Getting Worse

Mental Health of College Students Is Getting Worse | The Brink | Boston University (bu.edu)

“—-As a budding clinician of color, I think the tracking of these trends helps support efforts related to stigma reduction and [mental health] education that can be targeted toward certain communities,” says Jasmine Morigney

You indeed hit upon a serious issue, we continue in colleges and universities to teach one another “there is” a stigma to mental illnesses. Nor are we the least bit shy about it. The harm we do is readily observable, we choose not to look.

Historically rape/stigma took an entirely different path, whisper and innuendo. This version is an in your face college curricula related approach. And curiously it encounters no objection, not from students, not from administrators and not from professors themselves. Other versions have found disfavor, this one has not.

Harold A Maio

Why is (or should) mental health care becoming the job of universities or colleges? The amount of resources that need to be set up to provide such care jacks up the price of attending college and is not really the role of the academy. Professors are ill equipped to deal with student mental health problems and frankly should not have to because it is not their job.

Would we, as a society, expect our workplaces to have in-house mental health practitioners on site for the benefit of workers’ mental health? No. We’d expect individuals with mental health issues to use their health insurance to obtain such care. Why do we expect something different from universities?

And why are parents sending their children with mental health issues away from home and the health care that the student needs?

Finally, why as a society are we creating so many unresilient people these days?

I get the feeling I’m talking to a brick wall, but here goes.

Nothing in the research indicates it’s “the job” of colleges and universities to provide mental health care. Colleges and universities are increasingly offering SUPPORT, which is done out of a sense of human compassion, something that is glaringly lacking in the expressed opinions offered in your response. For most students, college is much more than academic instruction for the purposes of getting a degree- it is an experience in engaging with others and developing a sense of connection with others in a productive and satisfying way. As a retired Educational Administrator, among the knowledge, skills, and dispositions required for a position, perhaps the most crucial in considering a hire was dispositions, as the roles my employees would play require collaboration. Colleges and universities do this in explicit and implicit ways. If there are mental health issues, it is not only human compassion to offer support at the college level, it will better prepare these students to enter the workforce, which at least in part is what college is about.

Finally, regarding society creating unresilient people- these issues have always been out there but for decades were largely ignored. The result was a survival tactic which often included avoidance and denial which typically further resulted in a rather cold, unfeeling disposition, the likes of which I see in your response. As our society has evolved (thank heavens), we realize the wholeness in the human animal- not just a person who is required to output certain performances in work and family but as someone who has emotional needs which, when met, create better societies.

The point you’re missing is that academic and university life is severely CONTRIBUTING TO and CREATING mental health problems in students. Rigorous demands and expectations without any support or consideration of mental health leads to depression, burn out, anxiety, imposter syndrome etc. This is the reality for most students. And though I think its’s great universities now have some resources for mental health support or referral, when it comes to actual changes in policy that would help to improve student quality of life or prioritize work-life balance, it is all lip service. No academic program actually cares about that. hey all care about taking your money and saying we are highly rated. Not to mention the impact of COVID-19. Living through a global pandemic has increased feelings of isolation, stress, and fear all the while most programs haven’t made any significant changes in workload or demand. I’m currently in grad school at BU and professors have openly said “hating your life is just part of grad school. you’re stressed and drowning and then it’s done.” Basically telling people to get over it. I know people who had deaths in their family and were pressured to return to classes and work over being with their family and attending a funeral. This the culture of academia. They love to say they care about supporting students, but when students are actually in crisis it’s all about soldiering through it.

Also, I have my insurance through the university, therefore it is their obligation to help provide and refer me to health services. Many students are insured this way and in Massachusetts it’s specifically required all full-time students have some form of health insurance. So parents aren’t sending their kids with mental health issues away from care. Is society creating unresilient people, or do we as society prioritize work and productivity over mental wellness?

I’m guessing your post as “Anonymous” is directed at the first “Anonymous” and are not one and the same person, as your post contains a great deal of compassion and makes points which are reasonable. I agree that University life does create stresses and anxiety, and in this age of social media, even more so. If we had social media when I went to college, I’m not sure I would have made it without some professional help. I might be exaggerating, as I totally loved college.

I sincerely regret your experience with professors in Grad School at BU; hell, that’s almost a depraved indifference if someone commits suicide as a result. I would report these professors if I were in your shoes, but that may very well cause even more stresses.

I appreciate your thoughts. Best of everything to you in your continued life journey.

As someone who lives/thrives with depression, I find the comment by “Anonymous” very callous and without compassion. I did not ask for depression. It does run in my family and is largely caused by a hormone imbalance…NOT by my inability to handle stress. As a result, I am GRATEFUL that the company I now work with has been so patient and helpful in my process to learn how to deal with frustration without sounding like I am angry at my coworkers when I speak (yes, high functioning Asperger’s also). My mental health issues are genetically inherited. And I have a strong faithful family who supports me as well. I wish I had started asking for psychiatric help in college… But I have throughout my entire “adult life”, and I am a much stronger, more confident person. Why would we not want young people to learn IN COLLEGE that sometimes we need medical help to stay on the track to becoming better equipped to handle whatever life throws at you?! I’ve endured losing my roof to a tornado, living/working near the OKC Bombing, losing our home to a Hurricane… I am a strong and confident person…but it has taken every resource available to me to get there…I am not self-made! It really does take a village! And no, we are not wealthy people, especially since Katrina…but I did go back to full time work in order to assist my kids in getting the education they need to follow their passions and become mature, responsible adults. I get that it is a struggle to pay for a college education. But, it is WORTH THE WORK and I will keep advocating for EVERYONE to get the help they need through all of their life experiences.

Hey Julia, I appreciate your comment, as well as your sharing of personal experiences and how you’ve dealt with them. I realize it’s been quite a bit since you made this comment but I’m writing a college paper right now and would love to quote you on it. I do have on question like I would like you to answer regarding your comment and personal experiences. If that’s okay with you, please contact me at [email protected]

well I would first like to say that your comment is very inconsiderate of other people I can tell you have not gone through a hard time yet. They are not asking professors to be mental health doctors but to simply bring it up so that it does not seem so foreign to students and I.E. people such as yourself. Some people don’t exactly know what a mental health decline may look like or how to treat it. Mental health can decline at any moment depending on the situation and other surrounding factors so it’s nice to talk about it to get the discussion going and let people see different types. So many people commit suicide because they don’t know or didn’t have help or a simple person to talk to which is why we need to have the conversations open. A work field does have HR which can be used in many different ways including for your mental health so your argument definitely does have some weak points.

While I agree that “Professors are ill equipped to deal with student mental health problems and frankly should not have to because it is not their job,” professors (particularly early career) are often ill equipped to manage and/or mentor even their own graduate students. Part of the *responsibility* of professors that take on graduate students *should* be some career development via networking with the advisor colleagues, learning directly from experts (including their advisor, not just reading through manuscripts). All departments have different standards. Some departments do have written policies regarding advisor responsibilities while others allow advisors to be their own final judges. It’s a bit of a mess. But yes, advisors are not trained to deal with mental health issues, and it should not be a primary responsibility. Again, part of the problem is that the advisor-student environment itself can cause unnecessary anxiety. Some advisors are poor communicators, some are a bit passive-aggressive, some dole out projects not really in their field. Look at it this way, the mental health and personal issues of the professors also shouldn’t get dumped on students, and they often do.

Academia doesn’t have a great record of transparency, a lot of issues get buried. It’s a weird place to be. Some of my friends have had great experiences, others dropped out. I was witness to those that did drop, and based on what I saw, they had every reason to. Bright students but the faculty they had to directly interact with were a bit on the cruel side. Everyone makes their own decision if they want to tolerate situations for 5 years in order to complete a PhD.

Grad school is supposed to be part self-learning, part career training, part job transitioning, part mental shift from student to professional. Some department do a great jobs, others fail. Again, there’s little oversight and every advisor has a different style. A lot more accountability would help, on all sides.

In the big picture, student’s mental health is suffering because, since Reagan, the USA is moving from a great middle class society to a hunger games oligarchy. All but the most privileged are conscious of the need to beat the competition to maintain the living standards of their parents. This transcends race and Covid.

Colleges can put undue pressure on students, and some do break down under the pressures of classes, papers due, tests, homework, life outside class. It’s alot to juggle, and colleges need to consider if drinking from a firehose is the best way to enforce a love of learning and produce healthy graduates. My own son went to a peer uni, and was a great high school student, I had no doubt he could succeed. But the pressure of a top competitive college wore him down over the 4 years. He graduated but the experience destroyed him. Wish I had never sent him to be a full time student. Now he is on depression meds and unable to function. Really useful college degree.

It is ironic that this study done at BU, where my daughter graduated 12 years ago. We send our children assuming as administrators take care of situations as best as they could. My daughter was bullied in a Catholic elementary school for the majority time she attended they didn’t know how to handle bulling back then…then after getting her BA from BU same year recession hit our country…no job she kept looking no luck….she continued her education and graduated w honors earned MPA by then after doing so many odd jobs stress level escalated while bill collectors are calling her to collect money that she didn’t have….then COVID hit and another obstacles in moving forward….my daughter isn’t the only adult there are so many as a country we all should be concerned address the issue urgently. This isn’t a single family crisis it is national emergency when our educated adults are suffering and unemployed when their parents are not getting the help they need instead of thinking about their own retirement or what we are going to be faced as we aging?

i believe mental health is very important to the human body. Without sustaining good health, it could be life changing. Ive seen people who struggle with it and they go through it. Its rough.

We should all find out first. What are the main factors that cause this mental health problem? Is it caused by too much consumption of information from social media? Or overloaded with home assignments from college? Or is it because of life’s injustices and discrimination? Is it because of the misuse of social media? Then we will know when and how we can work to reduce it step by step. I do believe that the only key to managing mental health comes first from parents’ education (homeschooling) and then from the school’s policies. Through appropriate and effective support from parents and schools, there are possibilities to reduce mental health problems. How? Parents should ask questions like, How do you feel about the teaching and learning? How do you get along with others? What are the biggest challenges you have right now? We believe you CAN solve it or them. What strategies and supports are required? School administrators and teachers should make sure to have better and more positive communication with their students.

I normally tell my college students that life is a challenge, not a choice. Only you have the power to solve everything. The key is to think and act positively. Avoid negative activities, emotions, thoughts, judgments, and revenge. Focus on your goals. Your future depends on your attitude and beliefs. Even the best and most expensive colleges will not make miracles for you. However, they may do their best to help you, and only you are the one who has the power to shape and create yourself. ASK YOURSELF: What are the best things that empower my knowledge and skills to grow? How do I do it? When and where do I do it? Who can help me do it? I must do it now. By this time, in this place With this strategy, with this person A positive mindset has the power to change everything.

Thank you so much for shining light on this. People often underestimate the importance of mental health, when in reality, it affects every single thing we do! College can be a very stressful experience. When you think about it, it’s usually our first encounter with the real world, the adult world, and being asked suddenly to decide what we want to do for the rest of our lives can be so intimidating. This is exactly why Universities need to work on good support systems. Finding those schools and highlighting them is quite literally our mission in Supportive Colleges. So, from the bottom of our hearts, thank you for making this post. The more people know the importance of mental well-being, the more we can tackle it from the root!

How does the recent research on college student mental health reveal differences in the prevalence and treatment of mental health issues based on race and ethnicity?

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Students Get Real About Mental Health—and What They Need from Educators

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• Perspectives
• Student Support

M ental health issues among college students have skyrocketed . From 2013 to 2021, the number of students who reported feelings of depression increased 135 percent, and the number of those with one or more mental health problems doubled. Simply put, the well-being of our students is in jeopardy.

To deepen our understanding of this crisis, we asked 10 students to speak candidly about their mental health. We learned that the issues they face are uniquely theirs and yet collectively ours. We hope these responses will inform your teaching and encourage you to create safe classroom spaces where students feel seen and supported.

Students Share Their Mental Health Struggles—and What Support They Need

We asked these students and recent graduates, In what ways has your mental health affected your college experience, and how can professors better support you? Here’s what they had to say.

Elizabeth Ndungu, graduate student in the School of Professional Studies at Columbia University, United States: My mental health has affected me deeply, and I have sought therapy (which is a big thing for me, as I was born and raised in Africa and therapy is a “Western” concept). I’m a caregiver, so unexpected medical emergencies happen a lot, which mentally stresses me out. However, my professors have given me the time I need to perform my best. They’ve listened.

In general, I think professors can better support students by

Observing and reaching out to students if they notice a pattern of behavior.

Being kind. Giving a student a second chance may very well change their life for the better.

Being supportive. Remember students’ names, learn one unique thing about them that’s positive, or connect with them on LinkedIn or other social media platforms and show them that they have a mentor.

I think schools can better support students by

Admitting diverse students. Don’t just say it—do it. Seek out ways to make the school population more DEIA (diversity, equity, inclusion, accessibility) friendly, especially at historically white colleges. Inclusivity should be everywhere.

Making DEIA initiatives a priority. If you are educating organizations’ next leaders, make sure DEIA initiatives are in each program and cohort. Each of our classes should be tied to knowledge, strategy, and DEIA and its impact.

Raising awareness around mental health. Provide onsite and remote resources for mental assistance, automate low complexity tasks that will cause stress to students, invest in your staff and resources, and ensure that they are happy. Because dealing with unhappy staff will make unhappy students.

Pritish Dakhole, sophomore studying engineering at Birla Institute of Technology and Science, Pilani, India: Mental health is still stigmatized in India. We do not have easy access to therapy sessions, and it is a difficult topic to talk about with family. Thankfully, the scenario is changing.

I have been affected both positively and negatively by my mental health. Positively, because I have become more open-minded and perceptive. Negatively, because it has drained my will to continue, made me tired from all the overthinking, and made me turn to harmful addictions to distract myself from the pain.

Professors and schools could provide better support through

Webinars and meetings that make students aware of the issues they face and how to tackle them.

Group sessions—preferably anonymous—to remove fear.

Feedback systems so that the college is made aware of the problems that lead to a bad mental state.

Flexible education systems that allow students to take breaks during periods of excessive burnout.

Ocean Ronquillo-Morgan, Class of ’21, studied computer science and business administration at the University of Southern California, United States: In February 2021, I called 911 twice in the span of two weeks. I thought I was dying. I felt confused, felt like my body was about to give way, then I called the paramedics. They hooked me up to an EKG and checked my pulse. It was the first time in my life that I experienced panic attacks.

I don’t think anything else could have been done at the classroom level besides extending deadlines in extenuating circumstances. That’s the unfortunate nature of post-education institutions—you still need to make it “fair” for all students.

Alberto Briones, Class of ’22, studied operations and information management at Northern Illinois University, United States: Mental health can be a touchy subject. I have experienced depression and anxiety, but just thinking about all the things I could miss in life if I gave up is what gave me the strength to keep going.

Something professors can do to support students’ mental health is give students time to study between tests. Sometimes professors schedule tests on the same day, and suddenly students must study for three or four exams, all in the same day. It becomes overwhelming and they have to prioritize what tests they need to study more for.

Anjali Bathra Ravikumar, sophomore studying management information systems at The University of Texas at Austin, United States: It is stressful to be an international student at a competitive university in a competitive major. I often find myself having breakdowns and calling my parents in a panic about my future. The relatively restricted job opportunities because of my visa status and uncertainty about whether I’ll be able to forge the career that I want are major reasons behind this.

I have noticed that a lot of my international-student friends are constantly hustling as well, since we feel that we always need to be 10 steps ahead and cannot afford to slow down.

The best thing that a professor can do for me is provide as much guidance as possible in their respective field. Most of my professors have done that. This helps weed out some of the doubts that I have about potential career paths and gives me better clarity about the future. I feel that I cannot ask for more since I don’t expect everyone to be informed of what life is like for an international student.

Schools, on the other hand, can do a lot for us, such as tailor career management resources, offer international student group counseling (I attended one session and it was very liberating), provide financial relief (this is the absolute best thing that can be done for us) during rough times such as COVID-19. For example, when millions of international students had to take online classes during the pandemic, schools could have offered reduced tuition rates.

Something else that can seem small but goes a long way is using inclusive language in university announcements and communication. Most of the emails that we receive from the university feel more tailored to or are directly addressing in-state students (especially when major changes were happening at the beginning of the pandemic), and it is natural for us to feel left out. It might be a simple thing, but a couple of lines at the end of each email announcement with links addressing our specific concerns would make a lot of difference to us since we wouldn’t have to do our own research to figure out what it means for us.

EDUCATE YOURSELF BEFORE DIVING INTO MENTAL HEALTH TALKS

Starting a mental health conversation with students before we are prepared can be harmful. Here’s some advice from “ It’s Time We Talk About Mental Health in Business Classrooms ” by Bahia El Oddi, founder of Human Sustainability Inside Out, and Carin-Isabel Knoop, executive director of the Case Research and Writing Group at Harvard Business School, on how to get ready for these critical conversations.

Learn to talk about mental health. Enhance your mental health literacy through free resources such as the Learn Mental Health Literacy course (specifically for educators), the World Health Organization , and the National Institute of Mental Health . Consult the CDC for language about mental and behavioral health and the American Psychiatry Association for ways to describe individuals presenting with potential mental health disorders .

Reflect on your own biases. Consider how your own story—being raised by a parent with a mental health disorder, for example—may influence how you react and relate to others. Determine your level of openness to discussing the struggles you or your loved ones face or have faced. While it is possible to discuss mental health in the classroom without these anecdotes or personal connections, the courage to be open about your own past can have a transformative effect on classroom discussion.

Understand students may need extra support. Make yourself accessible and approachable to your students from the start so you can establish trust early. Advise them to seek professional help when necessary.

Nick Neral, Class of ’18, studied marketing management at the University of Akron, United States: At the end of my first year of college, I decided to stop participating in Division I athletics and my mental health plummeted. After calling our campus counseling center and waiting six weeks for my first intake appointment, I was told I couldn’t start therapy for two more months, but I could get medication within a couple of days.

After getting prescriptions for an SSRI and Xanax, I never heard from another clinician at my school again. They had no clue if I got the meds, if I took them, how I was doing, and whether I was on campus every day.

When my mental health was at its poorest, I was very disconnected from my classes. I went to, I think, five or six out of 30 finance classes I had during the semester.

I think professors are in this mindset that 20 percent of the class will naturally excel, a majority will do well enough, and a small chunk probably can’t be saved. Sometimes we don’t need saving in the classroom, we just need professors looking out for our well-being. There’s more to the story when a kid doesn’t show up to 80 percent of their classes.

My experience—and seeing others go through similar events—led me to create a platform where therapists can create content and free resources at forhaley.com . Anyone can filter through the content based on how they’re feeling and what’s going on in their life without paying anything or creating an account.

Shreyas Gavit, Class of ’20 in the MBA program at Oakland University, United States: Mental health has affected me because I’ve been depressed and feel trapped; I can’t just go to my home country and come back to the United States whenever I need to. Instead, I have to wait on visa dates, which are a total mess.

Schools and professors could provide more guidance in understanding how immigration has been affected due to COVID-19.

Nigel Hammett, Class of ’19, studied industrial and systems engineering at North Carolina Agricultural & Technical State University, United States: Throughout college I faced mental stress—not only from school, like everyone, but also from many constant family issues going on back home that required my energy. At times, I learned how to push through my feelings and submerge myself in my schoolwork, although I should have unpacked my trauma and handled it in a more mature way.

Students need an environment that encourages inclusive, candid dialogue around how we are feeling. There’s a correlation between social and mental health to overall success in our respective careers.

Alek Nybro, Class of ’21, studied marketing at St. Edward’s University, United States: Anxiety shows up differently for every person. I consider myself to be high functioning. This means when the going gets tough, I dig down and keep pushing, but often to extents that aren’t physically, emotionally, or mentally healthy.

In school, I didn’t know when to step back and take a break. That’s probably my biggest regret about my college years.

Professors could help students by making everything iterative. There shouldn’t be a final grade for assignments or projects. If you want to go back and revise something for a better grade, you should be able to do so.

Patrick Mandiraatmadja, first-year graduate student studying technology management at Columbia University, United States: There are times when I have felt overwhelmed by the number of deadlines and exams crammed into a specific week or few days. I always want to put in my best effort to study, which can lead to less sleep and more anxiety. Then college becomes more about getting through assignments and exams just for the sake of it and less about the learning.

Because of the amount of work or busy work, I have less opportunity to go out and do the things that make me feel alive and excited about life—whether it’s being with friends, exploring my city, exercising, involving myself with professional and social networks outside of school, or simply taking a walk and enjoying my day.

Students want to know that our professors and schools care. Part of that is providing an environment where we can talk about our personal struggles. I also think professors and schools should update the policies on homework, assignments, and exams. Sometimes we may push through and neglect our mental health, not taking the time to care for ourselves, just to get through that homework or finish that exam. The added pressure causes us increased anxiety; it’s no wonder today’s young people are some of the most anxious and unmotivated compared to previous generations.

What We Learned from These Students

These students and young alumni offer an honest glimpse into how mental health struggles have affected their college experiences. Although every student faces their own unique—and sometimes complicated—challenges, we are learning that sometimes the best response is the simplest one.

We must show our students that we care. So lend an empathetic ear, offer that deadline extension, and turn your classroom into a safe haven for open discussion. Your students need it.

Special thanks to Justin Nguyen , founder of Declassified Media , for connecting HBP to these students and young alumni who volunteered to share their experiences.

Help shape our coverage: These students spoke candidly; now it’s your turn. What are the biggest challenges you face in addressing student mental health in and out of the classroom? What experiences have stood out to you? Let us know .

Elizabeth Ndungu is a graduate student in the School of Professional Studies at Columbia University.

Pritish Dakhole is a sophomore studying engineering at Birla Institute of Technology and Science in Pilani, India.

Ocean Ronquillo-Morgan is a member of the University of Southern California’s Class of ’21.

Alberto Briones is a member of Northern Illinois University’s Class of ’22.

Anjali Bathra Ravikumar is a sophomore at The University of Texas at Austin.

Nick Neral studied marketing management at the University of Akron and is a member of the Class of ’18.

Shreyas Gavit studied in the MBA program at Oakland University and graduated as a member of the Class of ’20.

Nigel Hammett studied industrial and systems engineering at North Carolina A&T State University and graduated as a member of Class of ’19.

Alek Nybro studied marketing at St. Edward’s University and graduated as a member of the Class of ’21.

Patrick Mandiraatmadja is a first-year graduate student studying technology management at Columbia University.

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Decoding the Mind: Basic Science Revolutionizes Treatment of Mental Illnesses

By Linda Brady, Margaret Grabb, Susan Koester, Yael Mandelblat-Cerf, David Panchision, Jonathan Pevsner, Ashlee Van’t-Veer, and Aleksandra Vicentic on behalf of the NIMH Division of Neuroscience and Basic Behavioral Science

March 21, 2024 • 75th Anniversary

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For 75 years, NIMH has transformed the understanding and treatment of mental illnesses through basic and clinical research—bringing hope to millions of people. This Director’s Message, guest written by NIMH’s Division of Neuroscience and Basic Behavioral Science , is part of an anniversary series celebrating this momentous milestone.

The Division of Neuroscience and Basic Behavioral Science (DNBBS) at the National Institute of Mental Health (NIMH) supports research on basic neuroscience, genetics, and basic behavioral science. These are foundational pillars in the quest to decode the human mind and unravel the complexities of mental illnesses.

At NIMH, we are committed to supporting and conducting genomics research as a priority research area . As the institute celebrates its 75th Anniversary , we are spotlighting DNBBS-supported efforts connecting genes to cells to circuits to behavior that have led to a wealth of discoveries and knowledge that can improve the diagnosis, treatment, and prevention of mental illnesses.

Making gene discoveries

Medical conditions often run in families. For instance, if someone in your immediate family has high blood pressure, you are more likely to have it too. It is the same with mental disorders—often they run in families. NIMH is supporting research into human genetics to better understand why this occurs. This research has already led to the discovery of hundreds of gene variants that make us more or less likely to develop a mental disorder.

There are two types of genetic variation: common and rare. Common variation refers to DNA changes often seen in the general population, whereas rare variation is DNA changes found in only a small proportion of the population. Individually, most common gene variants have only a minor impact on the risk for a mental disorder. Instead, most disorders result from many common gene variants that, together, contribute to the risk for and severity of that disorder.

NIMH is committed to uncovering the role of genes in mental disorders with the aim of improving the lives of people who experience them. One of the many ways NIMH contributes to the discovery of common gene variants is by supporting the Psychiatric Genomics Consortium (PGC)   . The consortium of almost 1,000 scientists across the globe, including ones in the NIMH Intramural Research Program and others conducting NIMH-supported research, is one of the largest and most innovative biological investigations in psychiatry.

Global collaborations such as the PGC are critical to amassing the immense sample sizes needed to identify common gene variants. Data from the consortium’s almost one million participants have already led to transformative insights about genetic contributors to mental illnesses and the genetic relationships of these illnesses to each other. To date, studies conducted as part of the consortium have uncovered common variation in over a dozen mental illnesses.

In contrast to common gene variants, rare gene variants are very uncommon in the general population. When they do occur, they often have a major impact on the occurrence of an illness, particularly when they disrupt gene function or regulation. Rare variants involving mutations in a single gene have been linked to several mental disorders, often through NIMH-supported research. For instance, a recent NIMH-funded study found that rare variation in 10 genes substantially increased the risk for schizophrenia. However, it is important to note that genetics is not destiny; even rare variants only raise the risk for mental disorders, but many other factors, including your environment and experiences, play important roles as well.

Because of the strong interest among researchers and the public in understanding how genes translate to changes in the brain and behavior, NIMH has developed a list of human genes associated with mental illnesses. These genes were identified through rare variation studies and are meant to serve as a resource for the research community. The list currently focuses on rare variants, but NIMH plans to continue expanding it as evidence accumulates for additional gene variants (rare or common).

Moreover, mental illnesses are a significant public health burden worldwide . For this reason, NIMH investments in genomics research extend across the globe. NIMH has established the Ancestral Populations Network (APN) to make genomics studies more diverse and shed light on how genetic variation contributes to mental disorders across populations. APN currently includes seven projects with more than 100 researchers across 25 sites worldwide.

Connecting biology to behavior

While hundreds of individual genes have been linked to mental illnesses, the function of most of these genes in the brain remains poorly understood. But high-tech advances and the increased availability of computational tools are enabling researchers to begin unraveling the intricate roles played by genes.

In addition to identifying genetic variation that raises the risk for mental illnesses, NIMH supports research that will help us understand how genes contribute to human behavior. This information is critical to discovering approaches to diagnose, treat, and ultimately prevent or cure mental illnesses.

An NIMH-funded project called the PsychENCODE consortium   focuses on understanding how genes impact brain function. PsychENCODE is furthering knowledge of how gene risk maps onto brain function and dysfunction by cataloging genomic elements in the human brain and studying the actions of different cell types. The PsychENCODE dataset currently includes multidimensional genetic data from the postmortem brains of thousands of people with and without mental disorders.

Findings from the first phase of PsychENCODE were published as a series of 11 papers   examining functional genomics in the developing and adult brains and in mental disorders. A second batch of PsychENCODE papers will be published later this year. These findings help clarify the complex relationships between gene variants and the biological processes they influence.

PsychENCODE and other NIMH-supported projects are committed to sharing biospecimens quickly and openly to help speed research and discovery.

Facilitating these efforts is the NIMH Repository and Genomics Resource (NRGR)   , where samples are stored and shared. NRGR includes hundreds of thousands of samples, such as DNA, RNA, and cell lines, from people with and without mental disorders, along with demographic and diagnostic information.

Another NIMH initiative to connect risk genes to brain function is Scalable and Systematic Neurobiology of Psychiatric and Neurodevelopmental Disorder Risk Genes (SSPsyGene) . This initiative uses cutting-edge techniques to characterize the biological functions of 250 mental health risk genes—within the cells where they are expressed—to better understand how those genes contribute to mental illnesses. By systematically characterizing the biological functions of risk genes in cells, SSPsyGene will empower researchers to learn about biological pathways that may serve as new targets for treatment.

Genes also affect behavior by providing the blueprint for neurons, the basic units of the nervous system. Neurons communicate with each other via circuits in the brain, which enables us to process, integrate, and convey information. NIMH supports many initiatives to study the foundational role of neural networks and brain circuits in shaping diverse mental health-related behaviors like mood, learning, memory, and motivation.

For instance, studies supported through a basic-to-translational science initiative at NIMH focus on modifying neural activity to improve cognitive, emotional, and social processing  . Similarly, another new funding opportunity encourages studies in humans and animals examining how emotional and social cues are represented across brain circuits  to help address a core deficit in many mental disorders. These studies will increase understanding of the biological mechanisms that support behavior throughout life and offer interventions to improve these functions in healthy and clinical populations.

Developing treatments and therapeutics

The gene discovery and biology-to-behavior programs described here will lay the foundation for delivering novel therapeutics. To be prepared to rapidly implement findings from this research, NIMH supports several initiatives to identify behavioral and biological markers for use in clinical studies and increase our ability to translate research into practice.

Through its therapeutics discovery research programs , NIMH advances early stage discovery and development studies in humans and early efficacy trials for mental disorders. Taking these efforts a step further, NIMH supports the National Cooperative Drug Discovery/Development Groups for the Treatment of Mental Disorders , which encourage public–private partnerships to accelerate the discovery and development of novel therapeutics and new biomarkers for use in human trials. Moreover, NIMH is one of several institutes and centers in the NIH Blueprint Neurotherapeutics Network  , launched to enable neuroscientists in academia and biotechnology companies to develop new drugs for nervous system disorders.

For the treatments of tomorrow, NIMH is building a new research program called Pre-Clinical Research on Gene Therapies for Rare Genetic Neurodevelopmental Disorders  , which encourages early stage research to optimize gene therapies to treat disorders with prominent cognitive, social, or affective impairment. In parallel, NIMH’s Planning Grants for Natural History Studies of Rare Genetic Neurodevelopmental Disorders  encourage the analysis of pre-existing data from people with rare disorders to learn about disease progression and enable future clinical trials with these populations.

NIMH's Division of Neuroscience and Basic Behavioral Science supports many different research projects that help us learn about genes and gene functions, how the brain develops and works, and impacts on behavior. By investing in basic neuroscience, genetics, and behavioral research, we're trying to find new targets for treatment and develop better therapies for mental disorders. We're hopeful these efforts will lead to new ways to treat and prevent mental illnesses in the near future and, ultimately, improve the lives of people in this country and across the globe.

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Research Identifies Characteristics of Cities That Would Support Young People’s Mental Health

Survey responses from global panel that included young people provide insights into what would make cities mental health-friendly for youth

As cities around the world continue to draw young people for work, education, and social opportunities, a new study identifies characteristics that would support young urban dwellers’ mental health. The findings, based on survey responses from a global panel that included adolescents and young adults, provide a set of priorities that city planners can adopt to build urban environments that are safe, equitable, and inclusive. 

To determine city characteristics that could bolster youth mental health, researchers administered an initial survey to a panel of more than 400, including young people and a multidisciplinary group of researchers, practitioners, and advocates. Through two subsequent surveys, participants prioritized six characteristics that would support young city dwellers’ mental health: opportunities to build life skills; age-friendly environments that accept young people’s feelings and values; free and safe public spaces where young people can connect; employment and job security; interventions that address the social determinants of health; and urban design with youth input and priorities in mind. 

The paper was published online February 21 in  Nature .

The study’s lead author is Pamela Collins, MD, MPH, chair of the Johns Hopkins Bloomberg School of Public Health’s Department of Mental Health. The study was conducted while Collins was on the faculty at the University of Washington. The paper was written by an international, interdisciplinary team, including citiesRISE, a global nonprofit that works to transform mental health policy and practice in cities, especially for young people.

Cities have long been a draw for young people. Research by UNICEF projects that cities will be home to 70 percent of the world’s children by 2050. Although urban environments influence a broad range of health outcomes, both positive and negative, their impacts manifest unequally. Mental disorders are the leading causes of disability among 10- to 24-year-olds globally. Exposure to urban inequality, violence, lack of green space, and fear of displacement disproportionately affects marginalized groups, increasing risk for poor mental health among urban youth.

“Right now, we are living with the largest population of adolescents in the world’s history, so this is an incredibly important group of people for global attention,” says Collins. “Investing in young people is an investment in their present well-being and future potential, and it’s an investment in the next generation—the children they will bear.” 

Data collection for the study began in April 2020 at the start of the COVID-19 pandemic. To capture its possible impacts, researchers added an open-ended survey question asking panelists how the pandemic influenced their perceptions of youth mental health in cities. The panelists reported that the pandemic either shed new light on the inequality and uneven distribution of resources experienced by marginalized communities in urban areas, or confirmed their preconceptions of how social vulnerability exacerbates health outcomes. 

For their study, the researchers recruited a panel of more than 400 individuals from 53 countries, including 327 young people ages 14 to 25, from a cross-section of fields, including education, advocacy, adolescent health, mental health and substance use, urban planning and development, data and technology, housing, and criminal justice. The researchers administered three sequential surveys to panelists beginning in April 2020 that asked panelists to identify elements of urban life that would support mental health for young people.

The top 37 characteristics were then grouped into six domains: intrapersonal, interpersonal, community, organizational, policy, and environment. Within these domains, panelists ranked characteristics based on immediacy of impact on youth mental health, ability to help youth thrive, and ease or feasibility of implementation. 

Taken together, the characteristics identified in the study provide a comprehensive set of priorities that policymakers and urban planners can use as a guide to improve young city dwellers' mental health. Among them: Youth-focused mental health and educational services could support young people’s emotional development and self-efficacy. Investment in spaces that facilitate social connection may help alleviate young people’s experiences of isolation and support their need for healthy, trusting relationships. Creating employment opportunities and job security could undo the economic losses that young people and their families experienced during the pandemic and help cities retain residents after a COVID-era exodus from urban centers.  

The findings suggest that creating a mental health-friendly city for young people requires investments across multiple interconnected sectors like transportation, housing, employment, health, and urban planning, with a central focus on social and economic equity. They also require urban planning policy approaches that commit to systemic and sustained collaboration, without magnifying existing privileges through initiatives like gentrification and developing green spaces at the expense of marginalized communities in need of affordable housing.

The authors say this framework underscores that responses by cities should include young people in the planning and design of interventions that directly impact their mental health and well-being. 

“ Making cities mental health friendly for adolescents and young adults ” was co-authored by an international, interdisciplinary team of 31 researchers led by the University of Washington Consortium for Global Mental Health, Urban@UW, the University of Melbourne, and citiesRISE. Author funding is listed in the Acknowledgements section of the paper.

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Psychology professor leads field in HIV and mental health research

By Adrianne Gonzalez 03-29-2024

Steven Safren , professor of psychology and director of the Center for HIV and Research in Mental Health (CHARM) at the University of Miami, was recognized by the Faculty Senate with the  2023–24 Distinguished Faculty Scholar Award for a lifetime of distinguished accomplishments in clinical practice and research. 

After joining the University of Miami faculty in 2015, Safren founded CHARM — an interdisciplinary center between the College of Arts and Sciences, Miller School of Medicine, and the School of Nursing and Health Studies. Funded by the National Institute of Mental Health, the center is designated as a full HIV/AIDS facility and one of seven in the nation.

Nominated for the Distinguished Faculty Scholar Award by Philip M. McCabe , professor and chair of the Department of Psychology, Safren is lauded for his exceptional proactivity, extensive funding success, and leadership in the field. “He is a truly exceptional scholar, teacher, and University citizen. He has my highest recommendation,” said McCabe.

Safren earned his Ph.D. in clinical psychology from the University at Albany State University of New York and trained at Massachusetts General Hospital, Harvard Medical School specializing in cognitive behavior therapy. 

Reflecting on his most memorable moments at the University of Miami, Safren emphasizes his pride in witnessing his students' achievements during the commencement ceremonies and believes that both students and graduates must narrow their focus. “ Find a piece of what you are studying that you really enjoy, and do more of that,” he shared.

The 2023–24 Faculty Senate Awards Ceremony will be held in person on Monday, April 8, at 5 p.m. on the Coral Gables Campus.  Learn more about the awards ceremony.

This profile is part of a 2023–24 Faculty Senate Awards series recognizing all awardees.

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The Top 10 Bad Outcomes of Social Media Use, According to Students

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The downsides of social media use are getting a lot of attention in 2024.

The year started with Facebook founder Mark Zuckerberg getting grilled in a congressional hearing about the negative impact of social media use on children. The U.S. House passed a bill in March to ban the use of TikTok in the United States, and the Senate is considering a similar measure. And at the end of March, Florida Gov. Ron DeSantis signed one of the country’s most restrictive state social media bans for minors that is scheduled to go into effect in January.

Addressing adolescents’ worsening mental health recently has become a top priority for school, district, state, and federal leaders as young people struggle with record-high rates of depression and anxiety. And much of the conversation around the mental health crisis has centered on young people’s constant use of cellphones and social media.

“Children have been sold this belief that the more [social media] connections they have, the better off they are,” said Lisa Strohman , a clinical psychologist who specializes in technology-overuse issues and is featured in Education Week’s Technology Counts report. [But] their relationships are not deep, they’re not authentic.”

As part of its Technology Counts report, the EdWeek Research Center surveyed 1,056 high school students across the country about a whole host of issues related to social media use. The survey was conducted Feb. 9 through March 4.

One question asked students what negative consequences they had experienced as a result of their social media use. The question gave them 25 possible options to pick from. Here is a look at the top 10 answers:

1.    I believed information I later learned was fake.

2.    i was too tired to do what i needed to do because i didn't get enough sleep., 3.    i have used social media, but i cannot think of any negative outcomes i experienced as a result., 4.    i got in trouble with my parents/family/home., 5.    my self-esteem got worse., 6.    i was bullied., 7.    i embarrassed myself., 8.    i lost a friend or friends., 9.    it made me feel more isolated/alone., 10.    my grades/test scores got worse., sign up for the savvy principal, edweek top school jobs.

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Supporting mental health and wellbeing of university and college students: A systematic review of review-level evidence of interventions

Joanne deborah worsley.

1 Department of Primary Care and Mental Health, University of Liverpool, Liverpool, United Kingdom

Andy Pennington

2 Department of Public Health and Policy, University of Liverpool, Liverpool, United Kingdom

Rhiannon Corcoran

Associated data.

The authors have provided detailed information regarding their search strategy and the articles that were found. The information necessary to replicate the study is in the Supporting information files.

The review of reviews had three aims: (i) to synthesize the available evidence on interventions to improve college and university students’ mental health and wellbeing; (ii) to identify the effectiveness of interventions, and (iii) to highlight gaps in the evidence base for future study.

Electronic database searches were conducted to identify reviews in English from high-income OECD countries published between 1999 and 2020. All review-level empirical studies involving post-secondary students attending colleges of further education or universities that examined interventions to improve general mental health and wellbeing were included. Articles were critically appraised using an amended version of the AMSTAR 2 tool. Evidence from the included reviews were narratively synthesized and organised by intervention types.

Twenty-seven reviews met the review of reviews inclusion criteria. The quality of the included reviews varied considerably. Intervention types identified included: mindfulness-based interventions, psychological interventions, psychoeducation interventions, recreation programmes, relaxation interventions, setting-based interventions, and stress management/reduction interventions. There was evidence that mindfulness-based interventions, cognitive behavioural therapy (CBT), and interventions delivered via technology were effective when compared to a passive control. Some evidence suggested that the effects of CBT-related interventions are sustained over time. Psychoeducation interventions do not appear to be as effective as other forms of intervention, with its effects not enduring over time.

Conclusions

The review of reviews located a sizeable body of evidence on specific interventions such as mindfulness and cognitive-behavioural interventions. The evidence suggests that these interventions can effectively reduce common mental health difficulties in the higher education student body. Gaps and limitations in the reviews and the underlying body of evidence have been identified. These include a notable gap in the existing body of review-level evidence on setting-based interventions, acceptance and commitment training, and interventions for students attending colleges in UK settings.

Introduction

Poor mental health of further and higher education students is a growing public policy concern [ 1 , 2 ]. Recent research indicates that levels of common mental health difficulties, self-harm, and suicide are increasing among young people, especially young women [ 3 – 5 ]. There have been particular concerns about university students, with research and official figures suggesting that there has been an increase in the number of students experiencing mental health problems over recent years. Data on young people aged 16 to 24 years from three UK National Psychiatric Morbidity Surveys (2000, 2007, and 2014) highlighted that the prevalence of common mental health problems, suicide attempts, and self-harm was similar in students and non-students [ 6 ]. Between 2007 and 2014, however, the prevalence of common mental health problems increased in female students but not in female non-students. Although the prevalence of non-suicidal self-harm increased between 2000 and 2014 in both students and non-students, a smaller proportion of students than non-students reported suicide attempts [ 6 ]. US college students are also increasingly reporting common mental health problems and suicidality [ 7 ]. It is, therefore, important for educational institutions to offer accessible and effective interventions for their students.

Research suggests that young people’s mental health is poorer during university study than before entry. In a UK study, anxiety and depression were found to be higher at mid-course compared to one-month pre-entry into university [ 8 ]. Similarly, a UK cohort study found that levels of psychological distress increase on entering university and levels of distress did not return to pre-registration levels [ 9 ]. Other studies have also demonstrated that students’ mental health is poorer during their first year of study compared to pre-entry into university [ 10 ].

Concern around students’ mental health has prompted recent focus on mental health provision [ 11 ]. Services offered within educational institutions typically include either individual or group counselling. Although these services are well-positioned to provide mental health care, many college counselling centres across the US are under-resourced and operate at full capacity during much of the year [ 12 ]. According to an online survey of UK student counselling services, there was an increase in demand for support services over a three-year period in further education sectors [ 13 ]. Similarly, there has been an increase in the number of students seeking support from university counselling services [ 14 ]. Despite this increase, the capacity of professional services to offer 1 to 1 support to large numbers of students is limited [ 2 ]. Although requests for professional support have increased substantially [ 15 ], only a third of higher education students with mental health problems seek support from counselling services in the UK [ 16 ]. Many students do not seek help due to barriers such as stigma or lack of awareness of services [ 17 – 19 ]. Without formal support or intervention, there is a risk of further deterioration.

Given the increase in mental health problems among students and the surge in demand for formal support [ 1 , 20 , 21 ], reactive services alone cannot effectively support student mental health and wellbeing [ 11 ]. Educational institutions have recognised the need to move beyond traditional forms of support and provide alternative, more accessible interventions aimed at improving mental health and wellbeing. Such institutions have unique opportunities to identify, prevent, and treat mental health problems because they support multiple aspects of students’ lives. Although interventions exist to improve general mental health and wellbeing of students, research on the effectiveness of the various interventions has not been effectively synthesised to date. To address this, we conducted a review of review-level evidence to capture the largest body of existing research on general mental health and wellbeing interventions for college and university students. As there was a substantial body of reviews to be synthesised, the purpose of our review of review-level evidence was to summarise and synthesise this evidence and identify remaining gaps and limitations in the evidence base. This review of reviews aimed to: (i) synthesize the available evidence on interventions to improve college and university students’ mental health and wellbeing; (ii) identify the effectiveness of interventions, and (iii) highlight gaps for future study. The review of reviews explored two questions:

• What is the current evidence on interventions to improve the general mental health and wellbeing of college and university students?
• What does the evidence tell us about the effectiveness of current interventions and what interventions are likely to be the most effective?

Study identification

Search strategy.

We conducted a search of English language peer-reviewed literature of MEDLINE and MEDLINE In Process and other Non-Indexed Citations (via OVID) ; PsycINFO (via EBSCOhost) ; Social Science Citation Index (via Web of Science) ; and CINAHL Plus (via EBSCOhost) , from 1999 (01/01/1999) to 2020 (31/12/2020), which reflects review-level evidence of interventions before the global COVID-19 pandemic. Reference lists of all eligible reviews were hand-searched in order to identify additional relevant reviews (citation ‘snowballing’). Examples of each search strategy can be found in S1 File .

Inclusion and exclusion criteria

We included all review-level empirical studies (reviews of Randomised Controlled Trials [RCTs] and/or Non-Randomised Studies of Interventions [NRSIs]) involving post-secondary students attending colleges of further education or universities that examined interventions to improve general mental health and wellbeing. Both universal and indicated interventions aimed at improving mental health were included. Universal interventions are aimed at students without any pre-existing mental health problems, whilst indicated interventions are aimed at students who meet criteria for mild to moderate levels of mental health problems or have acknowledged an existing mental health problem, such as depression or anxiety. Thus, studies were included involving both general student populations and students with mental health problems. Studies were excluded if they examined interventions to address specific, pre-existing neurodevelopmental conditions (e.g., attention deficit hyperactivity disorder) or focused on non-health or wellbeing outcomes (e.g., educational performance outcomes). The search was limited to English language literature. Only peer-reviewed reviews published from year 1999 onwards from high-income countries of the Organisation for Economic Co-operation and Development (OECD) were included.

Titles and abstracts of publications were independently screened by two reviewers (JW and AP). Full-text copies of relevant reviews were obtained and assessed independently for inclusion by two reviewers (JW and AP). Any queries or disagreements were resolved by discussion or by recourse to a third reviewer (RC).

Assessment of methodological quality

All reviews that met the inclusion criteria were critically appraised using an amended version of the AMSTAR 2 tool [ 22 ]. The tool was amended to make it sensitive enough to differentiate between the various methodological standards of this particular body of evidence (see S2 File ). The reviews were quality assessed independently by two reviewers. Based on the results of the critical appraisal, reviews were then categorised as: (i) higher methodological quality (score 10 or above); (ii) moderate methodological quality (score 6 to 9); or (iii) lower methodological quality (score 0 to 5). This is a rating/categorisation of relative methodological quality across this body of evidence.

Data extraction and synthesis

The following data was extracted by the first author and checked for accuracy by the second author: aims, primary study design, setting/country, type of intervention, comparator (if any), population, outcomes reported, main findings in relation to the review questions, limitations, and conclusions specified by authors. Key findings from the reviews were tabulated and narratively synthesised [ 23 ]. Findings were grouped by intervention category, with evidence from higher methodological quality reviews reported first and in greater detail [following 24 , 25 ].

The search generated 4,006 records. Title and abstract screening resulted in 44 articles that met the study inclusion criteria. Full-text screening resulted in the inclusion of 27 reviews. Seventeen reviews were excluded as not meeting inclusion criteria (see S3 File ). A summary of our study selection process is presented in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Flow Diagram ( Fig 1 ).

Characteristics of the included reviews

The characteristics of included reviews are summarised within Table 1 . Information on setting (country) should be provided within Table 1 ; however, very few reviews specified the country in which interventions took place.

Overview of quality of included reviews

As shown in Table 1 , the methodological quality of the reviews varied. Using the AMSTAR 2 quality assessment tool, eleven reviews were categorised as higher methodological quality, ten reviews were categorised as moderate methodological quality, and seven reviews were categorised as lower methodological quality.

Findings of included reviews

1. mindfulness-based interventions.

A systematic review and meta-analysis of RCTs (rated as higher methodological quality) of different interventions for common mental health problems in 3396 university and college students found that MBIs were effective in reducing both depression and generalized anxiety disorder in the short term but were not durable [ 26 ]. In their meta-analysis, the authors found evidence that MBIs led to statistically significant reductions in depression (pooled effect size: -0.52, 95% CI: -0.88 to -0.16). Art, exercise and peer support interventions (-0.76, 95% CI: -1.19 to -0.32), and cognitive-behavioural related interventions (-0.59, 95% CI: -0.72 to -0.45) led, however, to greater reductions. They found no evidence that the effects of MBIs on depression were sustained over time. They also found evidence that MBIs significantly reduced anxiety (-0.49, 95% CI: -0.84 to -0.15) but, again, other interventions such as peer support and music (-0.84, 95% CI: -1.19 to -0.49) and CBT related interventions (-0.39, 95% CI: -0.55 to -0.22) led to greater reductions.

Another systematic review and meta-analysis of RCTs, which was graded as higher quality, examined the effectiveness of MBIs for mental health outcomes in 4211 post-secondary students [ 27 ]. Halladay and colleagues found evidence that MBIs significantly reduced symptoms of depression (Standardised Mean Difference [SMD] -0.49, 95% CI: -0.68 to -0.30), anxiety (SMD -0.53, 95% CI: -0.78 to -0.29), and perceived stress (SMD -0.39, 95% CI: -0.50 to -0.27) when compared to a passive control group (receiving no intervention/on waiting list). There was, however, no significant difference between the MBI intervention group in levels of depression, anxiety or perceived stress when compared to an active control group receiving health education, relaxation, physical activity, or other approaches including CBT.

Halladay et al. [ 27 ] also analysed the impacts of different lengths of intervention. They found that there was no significant difference in effects, for depressive symptoms, anxiety and stress, between brief and longer interventions. They also analysed the impact of traditional compared to adapted interventions (i.e., Mindfulness-Based Stress Reduction [MBSR] versus Mindfulness-Based Cognitive Therapy [MBCT] versus other or adapted MBIs), and found that MBCT (SMD: -1.21, 95% CI: -1.76 to -0.66) was more effective than both MBSR (SMD = -0.44, 95% CI: -0.72 to -0.16, p = 0.01) and other MBIs (SMD = -0.29, 95% CI: -0.45 to -0.12, p<0.01). When compared to no intervention, MBCT was found to be the most effective type of MBI.

Studies examining whether effects were sustained over time (follow-up studies) were split by type of intervention. Halladay et al. [ 27 ] found that MBCT interventions demonstrated sustained reductions in depression one month after (post-) intervention in two studies with a total of 64 participants (Mean Difference [MD] on the Beck Depression Inventory -5.06, 95% CI: -6.52 to -3.59). Other MBIs did not demonstrate sustained reductions in depression at one month or 2–3 months post-intervention in three studies (with a total of 374 participants), although reductions in depression were found at 4–5 months post-intervention in two studies (with a total of 191 participants; SMD -0.43, 95% CI: -0.72 to -0.14). MBCT interventions also demonstrated sustained reductions in anxiety symptoms at both 1-month in two studies (with a total of 66 participants; MD on Beck Anxiety Inventory [BAI] -7.12, 95% CI: -8.23 to -5.97) and 6 months in two studies post-intervention (a total of 65 participants; MD on BAI -5.95, 95% CI: -10.78 to -1.13). Other MBIs demonstrated significant reductions 1-month post-intervention in one study using a different measure (with a total of 33 participants; MD Hamilton Anxiety Scale -9.50, CI: -17.27 to -1.73).

A systematic review and meta-analysis of RCTs (rated as higher methodological quality) of MBIs for mental and physical health in university students found that MBIs were effective in reducing distress, depression and state anxiety when compared to passive controls [ 28 ]. In their meta-analysis, the authors found evidence that MBIs led to significantly significant reductions in distress (SMD -0.47, 95% CI: -0.60 to -0.34), depression (SMD -0.40, 95% CI -0.57 to -0.24), and state anxiety (MD -3.18, 95% CI -5.51 to -0.85) when compared to a passive control (receiving no intervention/waiting list). MBIs led to improvements in wellbeing (SMD 0.35, 95% CI 0.21 to 0.50) when compared to a passive control. Effects of MBIs lasted beyond three months for distress (SMD -0.32, 95% CI -0.50 to -0.13). When compared with active control groups, MBIs significantly reduced distress (SMD -0.37, 95% CI -0.56 to -0.18) and state anxiety (MD -5.95, 95% CI -9.49 to -2.41), but not depression (SMD -0.19, 95% CI -0.43 to 0.05) and wellbeing (SMD -0.08, 95% CI -0.43 to 0.27).

Ma and colleagues conducted a meta-analytic review of RCTs (rated as higher methodological quality) of MBIs [ 29 ]. They found that MBIs were effective in reducing depressive symptoms in university students (effect size: 0.52, 95% CI 0.39 to 0.65). The authors found evidence that universal MBIs (effect size: 0.41, 95% CI 0.28 to 0.55), selective MBIs (effect size: 0.44, 95% CI 0.18 to 0.70), and indicated MBIs (effect size: 0.88, 95% CI 0.64 to 1.11) led to significant reductions in depressive symptoms.

Bamber and Morpeth’s [ 30 ] review, graded as moderate quality, included a meta-analysis of evidence on the effects of MBIs on anxiety in 1492 college students. A number of primary study designs were included: studies with two-group comparisons (e.g., MBI versus control) and studies with pre-test and post-test analysis of MBI (one-group MBI). They found MBIs significantly reduced anxiety, compared to no-treatment controls (ES 0.56, 95% CI: 0.42 to 0.70, p<0.001). MBI groups’ pre and post intervention comparisons showed large significant reductions in anxiety. There was, however, a small but significant reduction in control group anxiety pre/post comparisons. They also found that higher numbers of sessions (number not specified) increased the effects of MBIs (p = 0.01), with more sessions leading to greater reductions in anxiety.

Fenton et al. [ 31 ] conducted a moderate quality systematic review of evidence on the impacts of different recreation programmes, including MBIs, on mental health outcomes in post-secondary students in North America. Randomised controlled trials, non-randomised with control, and non-randomised no control studies were all included. They found that mindfulness interventions reduced depression, anxiety, stress, and negative mood.

Conley et al. [ 32 ] conducted a moderate quality review and meta-analysis of evidence on the impact of universal mental health prevention programmes including MBIs for higher education students. The review included two study designs: quasi-experimental and random designs. They found that skill-training programmes with supervised practice were significantly more effective than both skill-training programmes without supervised practice and psychoeducation in reducing depression, anxiety, stress, and general psychological distress. Conley and colleagues found that relaxation interventions demonstrated the most overall benefit in terms of effectiveness, followed by mindfulness interventions and cognitive-behavioural interventions that did not differ from each other.

Regehr et al. [ 33 ] conducted a review and meta-analysis (rated as lower methodological quality) of evidence on the effectiveness of preventative interventions in reducing mental health outcomes in 1431 university students, including randomised and parallel cohort designs. Regehr and colleagues found that mindfulness-based interventions focussing on stress reduction significantly reduced symptoms of anxiety and depression. In their meta-analysis, mindfulness-based interventions were assessed for their impact on anxiety. They found that mindfulness-based interventions led to significant improvements, compared to control groups (SMD -0.73, 95% CI: -1.00 to -0.45).

Conley et al. [ 34 ] reviewed evidence on the effectiveness of 83 (controlled) universal promotion and prevention interventions (rated as lower methodological quality). These authors explored whether skill-orientated interventions were more effective with or without supervised skills practice. The authors also examined the effectiveness of different strategies employed in skill-oriented interventions such as cognitive-behavioural interventions, mindfulness interventions, relaxation interventions, and meditation in quasi-experimental and random designs. They found that skill-oriented interventions were more effective with supervised practice, and that supervised skills practice interventions reduced depression, anxiety, and stress. They found mindfulness interventions to be the most effective form among the skill-oriented programmes containing supervised practice. Mindfulness interventions were significantly more effective in comparison to other interventions (the proportion of all significant post-intervention outcomes combined was 78.8% for mindfulness, in comparison to psychoeducation [12.5%], cognitive behavioural [43.4%], relaxation [27.1%], meditation [13%], and other interventions [21.9%]).

Bamber and Schneider [ 35 ] explored the effects of MBIs such as Mindfulness Based Stress Reduction (MBSR) and Mindfulness Meditation (MM) on mental health outcomes including anxiety and stress in college students (rated as lower methodological quality). Both MBSR and MM were found to significantly reduce symptoms of anxiety and stress.

2. Psychological interventions (e.g., cognitive-behavioural interventions)

Huang et al. [ 26 ] conducted a systematic review and meta-analysis of RCT evidence (rated as higher methodological quality) on the effectiveness of interventions for common mental health difficulties in 3396 university and college students. They found that cognitive behavioural therapy (CBT) had significant positive effects on depression and generalized anxiety disorder. Meta-analysis results showed that cognitive-behavioural-related interventions led to greater reductions in depression (-0.59, 95% CI: -0.72 to -0.45) than mindfulness-based interventions (-0.52, 95% CI: -0.88 to -0.16) and attention/perception modification (-0.46, 95% CI: -1.06 to 0.13). Other interventions (art, exercise, and peer support) led to a greater reduction in depression (-0.76, 95% CI: -1.19 to -0.32). The follow-up (pooled) effect size of cognitive-behavioural related interventions (-0.75, 95% CI: -0.95 to -0.54) had a greater significant effect (the follow-up ranged from 2 weeks to 7 months post intervention).

CBT related interventions were associated with significant (pooled) reductions in anxiety (-0.39, 95% CI: -0.55 to -0.22). The pooled effect of other interventions (peer support and music; -0.84, 95% CI: -1.19 to -0.49) and mindfulness (-0.49, 95% CI: -0.84 to -0.15) for generalised anxiety disorder were associated with greater reductions in anxiety compared to CBT.

Winzer et al. [ 36 ] conducted a systematic review and meta-analysis (rated as higher methodological quality) to assess whether the effects of mental health promotion and mental ill-health prevention interventions were sustained over time. They found that CBT-related interventions led to significant (pooled) effects for 3–6 month and 13–18 month follow-ups in sub-group analyses for combined mental ill-health outcomes (-0.40, 95% CI-0.64 to 0.16; -0.30, 95% CI: -0.51 to 0.08, respectively). They also analysed impacts on combined positive mental health and academic performance at 3–6 months, and found that the interventions had significant effects (pooled effect size: 0.52, 95% CI: 0.06 to 0.98).

Cuijpers et al. [ 37 ] carried out a meta-analysis of evidence (rated as moderate methodological quality) that examined the effectiveness of different forms of psychological treatment, such as CBT and behavioural activation therapy (BAT), for addressing symptoms of depression in 997 college students. The review found a large overall (pooled) effect of the therapies versus controls (g = 0.89, 95% CI: 0.66 to 1.11). It also found that individual therapy was significantly more effective than group therapy (p = 0.003) but that type of treatment (CBT, BAT, or other) was not significantly associated with the size of effect.

In their review and meta-analysis (rated as moderate methodological quality) of the impact of universal mental health prevention programmes for higher education students, Conley et al. [ 32 ] found that skill-training programmes with supervised practice such as cognitive-behavioural interventions, mindfulness interventions, relaxation interventions, and meditation significantly reduced depression, anxiety, stress, and general psychological distress. Programmes without supervised practice were significantly less effective. Comparing the effectiveness of different interventions overall, they also found that relaxation interventions were the most effective (mean effect size: 0.55, 95% CI: 0.41 to 0.68), followed by CBT interventions (0.49, CI: 0.40 to 0.58), MBIs (0.34, CI: 0.19 to 0.49), meditation (0.25, CI: 0.02 to 0.53), and then psychoeducational interventions (0.13: CI: 0.06 to 0.21).

In their review and meta-analysis of evidence (rated as lower methodological quality) on the effectiveness of preventative interventions in reducing mental health outcomes in university students, Regehr et al. [ 33 ] found that cognitive and behavioural interventions focusing on stress reduction significantly reduced symptoms of anxiety and depression. In their meta-analysis, cognitive-behavioural interventions were assessed for their impact on anxiety. They found that cognitive-behavioural interventions (SDM -0.77, 95% CI: -0.97 to -0.57) led to significant improvement, compared to control groups.

Howell and Passmore [ 38 ] conducted a review and (‘initial’) meta-analysis (rated as lower methodological quality) on the impacts of ACT interventions for university student wellbeing (N = 585), including randomized controlled experimental designs. Their meta-analysis showed a small significant (pooled) effect on wellbeing (d = 0.29, 95% CI: 0.11 to 0.47, p = 0.008) when assessed with the Wellbeing Manifestations Measure Scale. ACT interventions were also found to reduce depression, anxiety, and stress.

Conley et al. [ 34 ] examined the effectiveness of different strategies employed in skill-oriented interventions such as cognitive-behavioural interventions, mindfulness interventions, relaxation interventions, and meditation (rated as lower methodological quality). Conley and colleagues found that interventions with supervised skills practice reduced depression, anxiety, and stress. Mindfulness interventions were found to be the most effective (78.8%) form of intervention among the skill-oriented programmes containing supervised practice, followed by cognitive-behavioural interventions (55.8%) which performed significantly better than relaxation (28.9%, OR = 3.11, p<0.01) and meditation (19.4%, OR = 5.26, p<0.001) interventions.

One review graded as lower quality reviewed evidence on the prevention and early intervention for mental health problems in higher education students found that CBT approaches are effective for prevention and early intervention [ 39 ]. The authors also reported that these approaches are effective for at least some months following the CBT intervention. The authors did not report the primary study designs they included.

In a literature review of studies of depression and treatment outcomes among US college students, graded as lower quality, brief individual cognitive therapy was found to be effective at reducing mild to moderate depressive symptoms [ 40 ]. This finding was based on only one RCT, however.

3. Psychoeducational interventions

In their review of RCTs (graded as higher methodological quality), Winzer et al. [ 36 ] explored whether the effects of mental health interventions (e.g., psychoeducational interventions) for students in higher education were sustainable over time. They did not find significant (pooled) effects on combined mental ill health outcomes at 3–6 months, 7–12 months, or 13–18 month follow-ups. They reported no superior effect of psychoeducational intervention. The 3–6 month and 13–18 month follow-up were, however, both only based on one study.

When Conley et al. [ 32 ] reviewed evidence on the impact of universal prevention programmes for higher education students, they found that skill-training programmes with supervised practice (0.45, CI: 0.39 to 0.52) were significantly more effective than both psychoeducation (information only) interventions (0.13, CI: 0.06 to 0.21) and skill-training programmes without supervised practice (0.11, CI: -0.01 to 0.22) in reducing depression, anxiety, stress, and general psychological distress (rated as moderate methodological quality). Psychoeducational interventions yielded significant effects for several mental health related outcomes including anxiety, stress, and general psychological distress (ESs>0.13). However, these interventions did not yield significant effects for depression, social and emotional skills, or interpersonal relationships. Psychoeducational interventions were found to be less effective than relaxation interventions, cognitive-behavioural interventions, mindfulness interventions, and meditation. Although interventions with supervised skills practice produced a significant positive effect averaged across all types of outcomes at follow-up (0.28, CI: 0.16 to 0.40), psychoeducational interventions did not.

In their 2013 review (graded as lower methodological quality), Conley et al. [ 34 ] explored whether skill-oriented interventions that included supervised skills were more effective than psychoeducational programmes. They found that psychoeducational programmes were not as effective as preventive interventions for higher education students.

3a. Educational/personalised feedback interventions

In their review (rated as lower methodological quality) of prevention and early intervention for mental health issues in higher education students, Reavely and Jorm [ 39 ] reported mixed findings on the effectiveness of educational/personalised feedback interventions.

Miller and Chung [ 40 ] explored treatment for depression and found that an intervention using personalised mailed feedback was effective at reducing symptoms of depression (rated as lower methodological quality). This finding was only based on one study, however.

4. Recreation programmes

In their review of RCTs (rated as higher methodological quality) on the effectiveness of interventions for common mental health difficulties, Huang et al. [ 26 ] found that recreational interventions including exercise, art and peer support were effective treatments for depression and anxiety. Although both CBT and MBIs were found to be effective, other interventions (i.e., art, exercise, and peer support) showed larger effects for both depression and generalized anxiety disorder.

When exploring the combined effects of yoga, meditation, and mindfulness on depression, anxiety, and stress in 1373 tertiary education students, Breedvelt et al. [ 41 ] found moderate positive effects for yoga, meditation, and mindfulness on symptoms of depression, anxiety, and stress (rated as higher methodological quality). They found no significant differences in subgroup analysis when they compared the effectiveness of yoga, mindfulness meditation, and MBSR. A small number of the included studies (N = 6) provided long-term follow-up data which ranged from 1 to 24 months. The (pooled) effect at follow-up was found to be small to medium (g = 0.39, 95% CI: 0.17 to 0.61).

A network of meta-analysis of RCTs (rated as higher methodological quality) of exercise interventions for depression in 2010 college students found that exercise interventions were effective in reducing depression [ 42 ]. When compared with usual care, Tai Chi (SMD = -11, 95% CI -16 to -6), yoga (SMD = -9.1, 95% CI -14 to -4), dance (SMD = -5.5, 95% CI -11 to -0.39) and running (-6, 95% CI -10 to -1.6) interventions were effective in reducing depressive symptoms. The authors found Tai Chi to be the most effective exercise intervention followed by yoga.

Fenton et al. [ 31 ] reviewed evidence on the impacts of recreation programmes such as mindfulness, meditation, Tai Chi, yoga, exercise, and animal therapy on mental health outcomes in post-secondary students in North America (rated as moderate methodological quality). They included a number of different primary study designs: non-randomised with control, non-randomised no control, and RCTs. They found that mindfulness, yoga, meditation, exercise, and animal therapy all reduced depression, anxiety, stress, and negative mood.

The review of evidence (rated as moderate methodological quality) on the impact of universal mental health prevention programmes by Conley et al. [ 32 ] found that meditation interventions were more effective than psychoeducational interventions but less effective than relaxation, cognitive-behavioural and mindfulness interventions.

The review (rated as lower methodological quality) by Conley et al. [ 34 ] also examined the relative effectiveness of different approaches used in skill-oriented interventions, including cognitive-behavioural, mindfulness, relaxation, and meditation. They reported that mindfulness interventions were more effective than cognitive-behavioural interventions, relaxation interventions, and meditation; and found that cognitive-behavioural interventions were more effective than both meditation and relaxation interventions which did not differ significantly from each other.

5. Relaxation interventions

In their review of universal mental health prevention programmes for higher education students (rated as moderate methodological quality), Conley et al. [ 32 ] found relaxation interventions to be the most effective. In contrast, Conley et al [ 34 ] examined the relative effectiveness of different strategies used in skill-oriented interventions including cognitive-behavioural, mindfulness, relaxation and meditation, and found that mindfulness interventions and cognitive-behavioural interventions were more effective than relaxation interventions, and that meditation and relaxation interventions did not differ significantly from each other (rated as lower methodological quality).

6. Setting-based interventions

Fernandez et al. [ 43 ] conducted a systematic review of evidence (rated as moderate methodological quality) on the mental wellbeing impacts of setting-based interventions for university students. They included experimental (e.g., RCT) and observational (e.g., controlled trial without randomisation, pre-post/before and after, and time series) study designs. Academic-based interventions, to enhance learning and teaching, were found to significantly improve mental wellbeing.

7. Stress management/reduction interventions

A systematic review and meta-analysis (rated as higher methodological quality) of stress management interventions for college students found that stress reduction interventions were effective in reducing distress [ 44 ]. In their meta-analysis, the authors found evidence that stress management interventions were effective in reducing stress (g = 0.61, 95% CI 0.30 to 0.93), anxiety (g = 0.52, 95% CI 0.25 to 0.78), and depression (g = 0.46, 95% CI 0.16 to 0.77) for students with high stress levels. The authors found evidence that the effects of stress management interventions were sustained over time. The effect of stress management programmes for students with high stress levels remained up to the 12-month follow-up (g = 0.40, 95% CI 0.21 to 0.60). Stress management interventions were also found to be effective in reducing depression (g = 0.36, 95% CI 0.21 to 0.51), anxiety (g = 0.52, 95% CI 0.36 to 0.68), and stress (g = 0.58, 95% CI 0.44 to 0.73) in an unselected college student population.

Yusufov et al. [ 45 ] conducted a meta-analysis (rated as lower methodological quality) of evidence on the impacts of stress reduction interventions. In their meta-analysis of stress reduction interventions, the authors found that stress reduction interventions were effective in reducing anxiety and stress.

Interventions delivered via technology

Different categories of interventions (e.g., CBT) can be delivered through different means. Harrer et al. [ 46 ] systematically reviewed and performed a meta-analysis of evidence (rated as higher methodological quality) on the impacts of internet interventions on symptoms of common mental health problems, wellbeing and functional outcomes among university students. Small effects from internet interventions were found on depression ( g = 0.18, 95% CI: 0.08 to 0.27), anxiety ( g = 0.27, 95% CI: 0.13 to 0.40), and stress ( g = 0.20, 95% CI: 0.02 to 0.38). There were, however, no significant effects on wellbeing. The effects were higher for interventions that were based on CBT principles.

Similarly, Davies et al. [ 47 ] reviewed evidence on the effectiveness of computer-delivered and web-based interventions in improving depression, anxiety, and psychological wellbeing in 1795 higher education students (rated as higher methodological quality). When compared to an inactive control group (receiving no-treatment or on a waiting list), sensitivity meta-analyses showed that interventions significantly improved anxiety (Pooled SMD −0.56; 95% CI: −0.77 to −0.35, p <0.001), depression (SMD −0.43; 95% CI: −0.63 to −0.22, p <0.001), and stress (SMD −0.73; 95% CI: −1.27 to −0.19, p = 0.008). The sensitivity analyses showed no significant effects for anxiety or depression, however, when compared to the active control group (in which participants received materials designed to mimic the time and attention received in the intervention group). Sensitivity analyses also showed no significant difference between the computer and web-based intervention for anxiety or depression when compared to comparison interventions that included a face-to-face version of the intervention, a web-based stress management intervention, another computer-based CBT program, and an online support group.

Lattie et al. [ 48 ] conducted a systematic review of evidence (rated as moderate methodological quality) on the effectiveness of digital mental health interventions on mental health outcomes in college students. All study designs were included. They found that digital mental health interventions can be effective for improving depression, anxiety, and psychological wellbeing among college students.

Conley et al. [ 49 ] conducted a meta-analytic review of evidence on the impact of universal and indicated technology-delivered interventions (TDIs) targeting mental health outcomes in 4763 higher education students, including randomized and quasi-experimental study designs (rated as moderate methodological quality). Universal interventions are aimed at students without any pre-existing mental health problems whereas indicated interventions are aimed at students who meet criteria for mild to moderate levels of mental health problems or have acknowledged an existing mental health problem such as depression or anxiety. They found that both universal and indicated TDIs were significantly effective in reducing symptoms of depression, anxiety, and stress. Indicated interventions produced higher overall (mean) improvements (0.37, CI: 0.27 to 0.47, p<0.001) than universal interventions (0.19, CI: 0.11 to 0.28, p<0.001). Both universal (0.21, CI: 0.11 to 0.31, p<0.001) and indicated (0.39, CI: 0.29 to 0.50, p<0.001) skill-training interventions led to significant improvements. Interventions without skill training were, however, only significant among indicated interventions (0.25, CI: 0.01 to 0.49, p = 0.042). Three of the 22 universal interventions, and eight of the 26 indicated interventions, assessed outcomes at follow-up (ranging between 13 to 52 weeks, and 2 to 26 weeks, respectively). Both universal and indicated interventions sustained significant positive effects on mental health outcomes at follow up (0.30, CI: 0.06 to 0.54, p = 0.015; 0.49, CI: 0.31 to 0.67, p<0.001, respectively).

Farrer et al. [ 50 ] systematically reviewed evidence on the effectiveness of technology-based interventions for mental health outcomes in tertiary students (rated as moderate methodological quality). They included both randomized controlled trials and randomized trials (equivalence trials). In interventions targeting both depression and anxiety, they found that technology-based CBT was effective in reducing anxiety and depression, although to a lesser degree than traditional therapy with human contact.

Other evidence

Conley et al. [ 51 ] conducted a meta-analysis of evidence (rated as moderate methodological quality) on the impacts of indicated prevention programmes for various forms of early-identified mental health problems such as sub-threshold depression and anxiety symptoms. Although they report significant effects, they provided insufficient information on the type of interventions to be categorised.

Rith-Najarian et al. [ 52 ] conducted a systematic review of evidence (rated as moderate methodological quality) on the effectiveness of preventative interventions in reducing depression, anxiety, and stress in university students. Rith-Najarian and colleagues found that prevention programmes reduced symptoms. The average effect sizes for preventative programmes were moderate (g = 0.65, 95% CI 0.57 to 0.73) regardless of delivery format or prevention level. According to delivery format, the effect sizes were similar for group (g = 0.69, 95% CI 0.58 to 0.81), self-administered (g = 0.65, 95% CI 0.50 to 0.81), and online/computer-delivered (0.52, 95% CI 0.41 to 0.63). According to prevention level, effect sizes differed for universal (0.69, 95% CI 0.55 to 0.83), selective (0.73, 95% CI 0.59 to 0.87), and indicated (0.53, 95% CI 0.44 to 0.63).

This review of reviews identified a range of interventions for student mental health and wellbeing, including mindfulness-based interventions (MBIs), psychological interventions (e.g., cognitive-behavioural therapy; CBT), psychoeducation interventions, recreation programmes, relaxation interventions, and setting-based interventions (e.g., academic and curriculum-based strategies). There was evidence that MBIs, CBT, and interventions delivered via technology were effective when compared to a passive control. There is some evidence to suggest that the effects of CBT-related interventions are sustained over time. The effects of interventions delivered via technology were found to be higher for interventions that were based on CBT principles in one higher quality review. Although technology-based CBT was effective in reducing depression and anxiety, traditional therapy with human contact was found to be more effective.

Moving beyond CBT, recreation programmes were also found to be effective. In fact, while both CBT and MBIs were found to be effective, other interventions (i.e., art, exercise, and peer support) were found to be more effective in one higher quality review. The review-level evidence suggests that psychoeducation interventions are not as effective as other interventions such as MBIs, cognitive-behavioural interventions, relaxation interventions, and meditation. The effects of psychoeducation interventions do not appear to sustain over time.

The review of reviews only located single reviews of evidence on acceptance and commitment training interventions [ 38 ] and setting-based interventions such as developing curricula to support wellbeing [ 43 ]. Although these interventions were shown to be effective, it should be noted that some of these reviews only included a small number of studies with small sample sizes [e.g., 38 ], and their findings should be viewed with some caution.

Limitations in the review of reviews

This is the first review of reviews to synthesise evidence on interventions to improve college and university students’ mental health and wellbeing. Despite every effort to gather the best evidence available, the review had several limitations. First, as our searches were limited to English language literature, we did not include evidence from studies reported in other languages. Identification and synthesis of evidence published in other languages is therefore desirable, although this would require sophisticated, technical, multilingual skills during study identification, appraisal and synthesis. Second, the searches were limited to a 21-year date range (1999 to 2020). Although this date range was deemed appropriate as we aimed to identify interventions that are most relevant to modern student populations and contexts, it should be noted that this review of review-level evidence reflects the time period before the global COVID-19 pandemic. Last, scarcity of high quality evidence syntheses on interventions to improve student mental health and wellbeing led to our decision to analyse data from all 27 reviews. This decision impacts on the quality of evidence synthesised. Despite limitations in the methodological strength of some evidence, the search identified a substantial group of higher methodological quality reviews and a large number of systematic reviews and meta-analyses. It should, therefore, be used to inform policies and practice alongside other considerations.

Gaps and limitations in the body of evidence

Although there was a large body of evidence on specific interventions such as mindfulness and cognitive-behavioural interventions, review-level evidence was limited in relation to other interventions such as setting-based interventions and acceptance and commitment training. Therefore, further primary studies examining the efficacy of setting-based interventions and acceptance and commitment training for students are required. Also, as there was a notable gap in the existing body of review-level evidence on interventions for students attending colleges in UK settings, a systematic review should be conducted in this area to identify primary level studies.

There are several limitations in the body of evidence. First, a number of the included reviews did not specify country and setting of the underlying evidence. It is likely that a substantial portion of the evidence is from US institutions, as this is typical for most evidence on health and wellbeing interventions. Another important limitation was that the included reviews only reported findings on beneficial effects of interventions. The underlying primary studies may have only attempted to assess efficacy and not the potential broader impacts of interventions. This is an important omission in the primary literature or the reviews. Interventions aiming for beneficial outcomes can often lead to unintended, adverse impacts for some participants. Primary and secondary research (including reviews) should attempt to identify adverse impacts so they can be eliminated or ameliorated, in accordance with the ‘first do no harm’ principle. A further limitation was that many of the included reviews did not consider the distribution of impacts from interventions across different population subgroups such as socio-economic status, age, gender, disability, and sexuality. As it is entirely possible that some interventions may work better for some students than for others, an evidence base that is more nuanced in terms of individual differences and differential impacts could underpin the tailoring of interventions to suit particular student characteristics leading, in time, to more suitable and effective interventions associated with nuanced, evidence-based delivery strategies. In addition to this, some of the included studies were lacking in detail on the nature of control groups. Greater detail on the nature of control groups should be provided in future studies. Last, few studies examined duration of effects over time. Future studies should routinely assess the duration of effects over time.

Implications

In light of the above, future primary and review-level research should carefully consider the distribution of impacts of interventions by population sub-groups, including socioeconomic, gender, ethnic, age, sexuality, and disability groups [ 53 ]. Intersectionalities between these population characteristics should also be considered. Cultural and faith backgrounds may also be important factors to consider. Future research should also explore latency and durability of effects overtime as some interventions, such as CBT, showed promise of effects sustained post intervention. This could include exploring further and longer pre and post intervention studies and studies exploring the impacts of top-up sessions. Moving beyond CBT, there are wider social determinant interventions which may be particularly important in this context such as debt or financial management, quality of student accommodation and housing, the competitive versus cooperative ethos of the learning environment, and sense of belonging to the student body and to the institution [ 54 ]. With the increasing prevalence of student mental health issues pointing to the influence of these wider determinants, it is clear that primary research in this area that takes note of the distribution of impacts is needed.

The review-of-reviews located a large body of evidence on specific interventions such as mindfulness and cognitive-behavioural interventions. The evidence suggests that these interventions can effectively reduce the common mental health difficulties of students. Evidence on other interventions was, however, limited. For example, although some work has begun developing curricula to support wellbeing, review-level evidence on organisational and structural interventions was limited. Thus, it is not currently possible to determine and rank which interventions work best, where and for whom, as this would require a larger body of evidence on certain intervention types, and comparative studies or reviews. Most of the included reviews did not consider the distribution of the intervention impacts (inequalities) for population subgroups such as age, gender, ethnicity, and socio-economic status. Noting the gaps and limitations in the review-level evidence previously identified, universities should select interventions based on the best available evidence, taking into consideration: the methodological strength of the underlying evidence, and the evidence on effectiveness. A good quality primary evidence-base examining these areas needs to be developed and then systematically reviewed before confident conclusions can be drawn about what works best to sustain positive mental health and wellbeing in today’s diverse and growing post-secondary student population. The need for effective support in this area can only have grown following the global COVID-19 pandemic and the associated disruption to teaching, learning, and university and college life. Following the disruption to teaching and learning, together with other stressors placed on young people from the COVID-19 pandemic, there is an imperative need to support students’ mental health and wellbeing. Future research in this area should elucidate the unique challenges that COVID-19 has presented for students to inform and tailor interventions for this generation and future cohorts facing disruptions to their teaching and learning experience.

Supporting information

S1 checklist, acknowledgments.

We would like to thank the review advisory group for their support and the What Works Centre for Wellbeing.

Funding Statement

The What Works Centre for Wellbeing Communities of Place evidence programme is funded by the Economic and Social Research Council (ESRC) and partners. The funders had no role in data collection and analysis, decision to publish, or preparation of the manuscript.

Data Availability